{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np  # 矩阵操作\n",
    "import pandas as pd # SQL数据处理\n",
    "\n",
    "from sklearn.metrics import r2_score  #评价回归预测模型的性能\n",
    "\n",
    "import matplotlib.pyplot as plt   #画图\n",
    "import seaborn as sns\n",
    "# 图形出现在Notebook里而不是新窗口\n",
    "%matplotlib inline\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##导入数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.344167</td>\n",
       "      <td>0.363625</td>\n",
       "      <td>0.805833</td>\n",
       "      <td>0.160446</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2011-01-02</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.363478</td>\n",
       "      <td>0.353739</td>\n",
       "      <td>0.696087</td>\n",
       "      <td>0.248539</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011-01-03</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.196364</td>\n",
       "      <td>0.189405</td>\n",
       "      <td>0.437273</td>\n",
       "      <td>0.248309</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2011-01-04</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.212122</td>\n",
       "      <td>0.590435</td>\n",
       "      <td>0.160296</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2011-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.226957</td>\n",
       "      <td>0.229270</td>\n",
       "      <td>0.436957</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr  mnth  holiday  weekday  workingday  \\\n",
       "0        1  2011-01-01       1   0     1        0        6           0   \n",
       "1        2  2011-01-02       1   0     1        0        0           0   \n",
       "2        3  2011-01-03       1   0     1        0        1           1   \n",
       "3        4  2011-01-04       1   0     1        0        2           1   \n",
       "4        5  2011-01-05       1   0     1        0        3           1   \n",
       "\n",
       "   weathersit      temp     atemp       hum  windspeed  casual  registered  \\\n",
       "0           2  0.344167  0.363625  0.805833   0.160446     331         654   \n",
       "1           2  0.363478  0.353739  0.696087   0.248539     131         670   \n",
       "2           1  0.196364  0.189405  0.437273   0.248309     120        1229   \n",
       "3           1  0.200000  0.212122  0.590435   0.160296     108        1454   \n",
       "4           1  0.226957  0.229270  0.436957   0.186900      82        1518   \n",
       "\n",
       "    cnt  \n",
       "0   985  \n",
       "1   801  \n",
       "2  1349  \n",
       "3  1562  \n",
       "4  1600  "
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('/home/yan/PycharmProjects/homework1/rent/day.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 731 entries, 0 to 730\n",
      "Data columns (total 16 columns):\n",
      "instant       731 non-null int64\n",
      "dteday        731 non-null object\n",
      "season        731 non-null int64\n",
      "yr            731 non-null int64\n",
      "mnth          731 non-null int64\n",
      "holiday       731 non-null int64\n",
      "weekday       731 non-null int64\n",
      "workingday    731 non-null int64\n",
      "weathersit    731 non-null int64\n",
      "temp          731 non-null float64\n",
      "atemp         731 non-null float64\n",
      "hum           731 non-null float64\n",
      "windspeed     731 non-null float64\n",
      "casual        731 non-null int64\n",
      "registered    731 non-null int64\n",
      "cnt           731 non-null int64\n",
      "dtypes: float64(4), int64(11), object(1)\n",
      "memory usage: 91.4+ KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "      <td>731.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>2.496580</td>\n",
       "      <td>0.500684</td>\n",
       "      <td>6.519836</td>\n",
       "      <td>0.028728</td>\n",
       "      <td>2.997264</td>\n",
       "      <td>0.683995</td>\n",
       "      <td>1.395349</td>\n",
       "      <td>0.495385</td>\n",
       "      <td>0.474354</td>\n",
       "      <td>0.627894</td>\n",
       "      <td>0.190486</td>\n",
       "      <td>848.176471</td>\n",
       "      <td>3656.172367</td>\n",
       "      <td>4504.348837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>211.165812</td>\n",
       "      <td>1.110807</td>\n",
       "      <td>0.500342</td>\n",
       "      <td>3.451913</td>\n",
       "      <td>0.167155</td>\n",
       "      <td>2.004787</td>\n",
       "      <td>0.465233</td>\n",
       "      <td>0.544894</td>\n",
       "      <td>0.183051</td>\n",
       "      <td>0.162961</td>\n",
       "      <td>0.142429</td>\n",
       "      <td>0.077498</td>\n",
       "      <td>686.622488</td>\n",
       "      <td>1560.256377</td>\n",
       "      <td>1937.211452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022392</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>183.500000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.337083</td>\n",
       "      <td>0.337842</td>\n",
       "      <td>0.520000</td>\n",
       "      <td>0.134950</td>\n",
       "      <td>315.500000</td>\n",
       "      <td>2497.000000</td>\n",
       "      <td>3152.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>366.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.498333</td>\n",
       "      <td>0.486733</td>\n",
       "      <td>0.626667</td>\n",
       "      <td>0.180975</td>\n",
       "      <td>713.000000</td>\n",
       "      <td>3662.000000</td>\n",
       "      <td>4548.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>548.500000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.655417</td>\n",
       "      <td>0.608602</td>\n",
       "      <td>0.730209</td>\n",
       "      <td>0.233214</td>\n",
       "      <td>1096.000000</td>\n",
       "      <td>4776.500000</td>\n",
       "      <td>5956.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>731.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.861667</td>\n",
       "      <td>0.840896</td>\n",
       "      <td>0.972500</td>\n",
       "      <td>0.507463</td>\n",
       "      <td>3410.000000</td>\n",
       "      <td>6946.000000</td>\n",
       "      <td>8714.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant      season          yr        mnth     holiday     weekday  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean   366.000000    2.496580    0.500684    6.519836    0.028728    2.997264   \n",
       "std    211.165812    1.110807    0.500342    3.451913    0.167155    2.004787   \n",
       "min      1.000000    1.000000    0.000000    1.000000    0.000000    0.000000   \n",
       "25%    183.500000    2.000000    0.000000    4.000000    0.000000    1.000000   \n",
       "50%    366.000000    3.000000    1.000000    7.000000    0.000000    3.000000   \n",
       "75%    548.500000    3.000000    1.000000   10.000000    0.000000    5.000000   \n",
       "max    731.000000    4.000000    1.000000   12.000000    1.000000    6.000000   \n",
       "\n",
       "       workingday  weathersit        temp       atemp         hum   windspeed  \\\n",
       "count  731.000000  731.000000  731.000000  731.000000  731.000000  731.000000   \n",
       "mean     0.683995    1.395349    0.495385    0.474354    0.627894    0.190486   \n",
       "std      0.465233    0.544894    0.183051    0.162961    0.142429    0.077498   \n",
       "min      0.000000    1.000000    0.059130    0.079070    0.000000    0.022392   \n",
       "25%      0.000000    1.000000    0.337083    0.337842    0.520000    0.134950   \n",
       "50%      1.000000    1.000000    0.498333    0.486733    0.626667    0.180975   \n",
       "75%      1.000000    2.000000    0.655417    0.608602    0.730209    0.233214   \n",
       "max      1.000000    3.000000    0.861667    0.840896    0.972500    0.507463   \n",
       "\n",
       "            casual   registered          cnt  \n",
       "count   731.000000   731.000000   731.000000  \n",
       "mean    848.176471  3656.172367  4504.348837  \n",
       "std     686.622488  1560.256377  1937.211452  \n",
       "min       2.000000    20.000000    22.000000  \n",
       "25%     315.500000  2497.000000  3152.000000  \n",
       "50%     713.000000  3662.000000  4548.000000  \n",
       "75%    1096.000000  4776.500000  5956.000000  \n",
       "max    3410.000000  6946.000000  8714.000000  "
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 各属性的统计特性\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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R08Sf3t/ndzgSpZRARICm1g7WVtQye1JGzNx53p8LZ+ZSlJvKva/vQBc0SiSUQESANbtq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\nIhIRJRAREYmIEoiIiERECURERCLy/wFMdYgcL9SQqAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5012936d50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.cnt.values, bins=30, kde=True)\n",
    "plt.xlabel('cnt', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Jes6MJy8CQGwAgpBjVK6gKtWPn6rIvZ0fc8/PWcKG1W6mDo6wca87fuN40+ILTAu3mK6X\nh0pgDjIDEIQWJKhgi/u3IB14YIEXQnW70U2jxm2ce2Gupkzj0J4h9G/sNxI2cdHR1YG+tX2Wesdz\n/qoaBBP7JgLblodKYA4iAAShxTAp2OL+bWLfRGACOB3uvPd+mUKDqJysVO0ESY6gF+YX8P2bv4+F\nWSu9g3Otpu+brunsVQZjlVHYO3sKm201a0g2UEFoMXQFW0rdJZx++rQ6lbOmgIluX8BS5lAAOHLt\nkVj081GKyjQDXdZQ5zopbSIEDFwzgHU3rAMQPttqkkg2UEHIKboRdOVkRTs6j5IAzun877rqLt/O\n3/HDNwmumpmeyUQQlfY62YJJV/R+6vBU9WvYbKtZRASAILQYUXTQVCAMF4brksDp9uV4CR259oh/\nfhwCtj+13RoVGygTyj3l1EfHfjiRyCYCM67KaWkiAkAQWgy/JG86eIGV3jlBXkJBap/SyhJGekcw\nXBg2SuMw+9ys0jOoEZwo3VJ3qS5SuVAsKKOXdfACY6R3RCvM3AJTKzxbyEgsRmBBaDG8fvTlnjJm\nn5s11tHPvTCHA5sPaPdlasgsFAt4cebF6nFNjMOVkxUc3HIQXSu6qgFWjeC1baiMskD9+Y3tGFPb\nIUhvn/AagAd3DfpGNbvJqrFYjMCCkAN0Bkk/l0avwVLVSWmNvwR0nRlPJ25CqbuE2Wdnq948qvaH\nQWfk1Y78V6s7bZOOPQ1jsRiBBaGNqEn97Epa5pe22G2wVAVnHdxyEBe97yKlaqfQUfDt/DfcviG2\nlMnUQRjaM4Sus5YKxFBhKQ9RFJWS6nppbRgEbDu+LXJnnWVjsaiABCEn6HLvjG4a1XZujsFS10lN\nHZ5CsVSs6+wX5/0Lpzht8XMzNYUXuG4E7WQNbSQ/j/d66dqq0+n7xWO495tlY7HMAAQhRxzaegjD\nhWEMk/X31Wu+6uud4xhxdZ30zPRMaDWPO+VzFIO1l6BKZHGNpk3TZjiYjuyzbCwWASAIOeHQ1kNW\nojZXhx/Uec8+O+s7Qg/qpArFQt33oT1D1e9BVcmCKC4vGhmXGx1NO7r8uRfmqiqvoNz/piP7sIIl\nSUQACEJOOLr3qPnKBHSt6KoxqnpxOildEZdSdwmX33p5jR798lsvr+sw+zf2Y9vxbUYFWArFgnU8\nQzuGQyOj6Rr7ByyVk3Pufmol05G9zj6TBS8gsQEIQosQ5HESJkfPhW+9EA+PPaz93Z28DbCigd0B\nYc5I3y/nv5f+jf2Yvm8aR/ceBS8wqIPQ+5ZenDp2KtA98u4P3a0VVo2Opv1UOX7nFsYNNMx1ShIR\nAILQApgYHHX5bVQ8/A195+/g7LeRWAF3+70upbzAOPHtE0ajYZ27us49MwxRjbQqgbZm85pMdvQ6\nRAAIQgugG6WOXjlarX3beUansqShkgA5UTlZweT+yRohYNKxqWYp0/dNY/ymceUxTUbaYzvGlOko\ndAnuwgZdaYvmBKiVJvdPYmLfRFXo8gJjYt8Eei7t0VZay1IQGCA2AEFoCfxGo05BFePO35CwnjWq\nWIK7rrqrzjDtJWikHWaErotn8IsViGqkNfECitKeJBEBIAgtQBQjZ3l12ThLp4qZR2ZCdVS6QvJB\nBJ2bibF1cv8kRnpHMHrlaOigq6hGWhPBlOUgMEBUQILQElSrcYXI3DIzPYN1N6xDz6U9VRVE2IIu\nd111l6W7P1UJVF9EdcUMGmkHGVtN6hmb6PPDqmVMVEdZDgIDZAYgYGn0pEoXLGSD/o39oTp/wAry\ncrbddnwbdi7urEbQmrI4t2gZbm31xeiVo9i9arfyGYnqihmUzsFvhD65fxIHNh9IpYyjieooy0Fg\ngOEMgIjOBvB5AL8K6zH8EIAfA/gSgF4AxwG8j5l/QUQEYA+AtQBeAPBBZv6evZ/NAD5h7/bTzLwv\ntjMRImEazi6kT3m1esSpY/bZ2RpDLqAftYbByegJ1D4jqpF6oVgAEfnGG5g8c6oRuvPsBs1o4gy6\ncht0SytLNeo1r+ssEM5VNA1MZwB7APw9M/8ygDUAHgJwHYAxZu4DMGZ/B4AhAH323xYANwIAEa0E\nsBPAGwC8HsBOInppTOchRCTrOkphicFdg3WRt34szC7U3cc4UjMA6mdENVK//NbLsf6W9dVgLl3N\ngCjPnGlx+bhcM70G3crJSo3hfb4yX7dNloPAAIMZABG9BMCbAXwQAJh5FsAsEa0H8BZ7tX0AvgXg\n4wDWA/gCW467/0JEZxPRufa69zLzKXu/9wJ4F4Avxnc6Qli0OspHZqwcMQ34fWfV9a1Vca5fGFuA\ncx+d6+/16XfURJVTFZRW1qdc9t23oR7bO3ofLgwr2x9WL266vso1MwpBAkfn0prVIDDATAX0SgBP\nAriViNYAOArgWgAvZ+afAQAz/4yIXmavfx6AR13bn7CX6ZbXQERbYM0c0NPTE+pkhPBoVQKuwhhh\n1UKiVmoOTjBVWFuA9/r7dUheFYefQPDqsU3vu/aZY9QIqyBM1VkmsQbe81ANXkwETlaMu6aYzCc7\nAVwM4EZmfh2A57Gk7lGhmuOxz/LaBcx7mXmAmQfOOeccg+a1L3EYb5UqAUVhjDBTdFErxY/TuZpW\n/fJiev3dBuPtT23H+lvWK3MBqfTYuvt+5NojNcv81FBh/OTDqLNMO2Y/v31ntuRHVoy7ppgIgBMA\nTjDz/fb3r8ASCD+3VTuw/z/hWv8C1/bnA3jMZ7kQgbgCTMIUxjB9ibLu+taKmOq7/Yhy/fs39mP7\nU9uXCrz46LF1+3eiit379EvypgqmUg10wmQaNe2YGxm8ZMm4a0qgCoiZHyeiR4no1cz8YwCDAH5k\n/20G8Bn7/932JvcA+B0iugOWwXfGVhF9DcCfuQy/7wBwfbyn0z5ETWClotHCGKr1GtleqCeo8y51\nlzBfmfcVEiqVjcoWoLLZeG0HTodo6mHkfS6dZ26YhpXrO+cbpFYyKTwTpmOOOngJykmUVZuYqUvB\n7wLYT0Q/APBaAH8Gq+N/OxFNAXi7/R0ADgP4KYBjAP4vgK0AYBt//xTAd+2/TzkGYSE8zRxlN5q/\nPMv5z1sVP+HpeAa5c9l7Fa7e66/yaHH7+3tnkyYzTr/76xijvfvURSk752s6Ivd77sN43fj57et+\now5C39o+jO0YU6pjs5wOwkgAMPMDtl7+15j5cmb+BTOfZOZBZu6z/5+y12Vm/igz/xIz9zPzuGs/\ntzDzq+y/W5t1Uu1AMwNMGnVdy7rrWyui03cXzyyCiKq2ASeX/cA1A9rAKV3KBDfeTtakI+7f2K+t\nHQDUd3xjO8bU6kZaEiamAx3t+7C6HOq58xu86O4BLzDGbxyv6eBHrxzFn5/15zi09ZAyUC0rNjFJ\nBdGiNDvApFHXtSy7vrUiupTMYzvG6lQfcy/M4cE7H0TXiq6a5SYpE9y4O1nTjnhoz5DvMdxqSu2o\nnZfO11SdGNf7YJL6+sDmA0bpNGafm7US4WmYeWQGw4XhVFVCIgBalDhytPuRVZ1lO6MSqqNXjirX\nrap0sDTy7ix1hjIkuztZ04645rn0qTPsu0+XUde0Y4/zfdANXpx3IkwupUCcGcOmUUzfN411N6yL\nb98GiABoYeIYZas6egCZ8+MXgVRPVYdu0B/NvTAXqvP3drJRql/pDLOOwdlkn2E69mbOOsPOnkLD\nwPhN47EErIVBBEAbo/OwUI0Uo3oYNbOdQHsHlml16A2i8miJMsIe3DWoVJd4cxTp9ukV+htu29DU\nDt7v3OJwww2E672lmg3pSq1lgYGBAR4f1+vQhMbwc51TQsDOxZ1Na4/uJdy9arcyAEpXEapd0KVU\n0FE8swgw/DuyGO/x5P5JrYoq6N6pRtzF5cWmOBOojlUoFrDsJcuqbrGNJtAzJqbrT0RHmXkgaD1J\nB93GhHUZbaYfv85V7tDWQ9ro13YJLNMFQoW9H4tzi1izeY1v4FSc99jPyyXo3iUZTa4rZON2i41a\nVAeAUaBadd2EY2VEBZRDTPXlpZUlfWoBj245bj9+bxtnn5tVvvBH9x7V7qMdAsv81F8qHbofC7ML\nmDo8hW3Ht2lH2HHeY79OPujeJRlNbrRPJ5mN553oLHX6pucodZcw+9ysUTvSiJWRGUBGiZrn59DW\nQxjdNBoYdDK5fxKnf3FavyOPaqGzFN9YQTXa171Efh4X7RBY5pdfx4m30KVYVuF0dknEamg7eQq+\nd0kWUjHeJ6Pmeq3ZvCZwk9lnZ43yN3Wc0ZFKrIzMADJIVKPn5P5JjN9UX4Dba8CtFtIIUR1KVwQk\nCmEMatShLmFY6i61hQE4KL+Ocw3qZgIa7yB3Z2fiNdOI95VyhkLAwDUDgfsw9TqKwzvMdCbltlsc\n2npI+a7VQDBOrb1weql2g3gBtTlR8/z4eYUEFao2wdQTyPtS9q3tw9Thqep3Y4Ma2TMAb2dGVgcY\nJnVwq2KSX0flTdO3tg8T+yYaUvE06n3ViG++ybZxeYepaiR402B7axAHdf6FYgGLc4vGbWik/Y0g\nXkAZROvdEeAh4OcVQh0EXuTGPRoC2mDkL60ZnZa6S+ha0bVkdGPFNgo9bJ7TTPh50vjdC6d2gKN+\nUJUrDEKbFDAj3lfNbJ/fzCLIe043azUljvabegHJDCCDRM2m6de5Ow9ko+5sQW0wml0o3o3i8mK1\ng1K+YOz5b5NmfEIS9G/sr+nI3Tj3QjXj8o7+VeUKdVT3FxDJq90uoWC9ZhqK/dRjvu8Q+dutTEjS\nu02MwBkkajbNuOq9AlC6vZm0IczDW+ouKQ2QzSoNmHV0hv+hPUPa50FlUB+/aTyyC2XN/jSoBgFp\nZLxM0lDscGjrIf8VYlCoJOndJgIgg0T10FAWd4mCQkVT6i4ZtSHMw3v66XovpMn9k6BCOKdrk0pN\nWcevA/V7HpQzrgA7kJ+HWdAMTjcISKMKXBppx/3ckuMgaVdQUQFllDB5TVSFPRw6zujAwmkzT4Qq\nig6ka0WXUXvC+Ka71VIHtxzE9H3TmNg3EXoK7U0t0IroOtDRK0cxtmMMg7sGlXrhMCq9ck850HDq\n67uvKXoyuX8ytLooDpqdEFGF37NZ6vaJqzEgip2mUUQAtDjeF9r9AMYZvm76IjsPr2nKXAcn6CuK\n/nRhdqHl7QB+11fnHeKbDE4TyBfkYeaXoVMlgJznT0ez1RlJpx0PMvAWlxcj5wwyHWTFiaiAWhTT\nwh5xEfQiu9UKYzvGcMmWS0LbIxoxnrW6HSDo+jqzgWFaUtv4FVTRFYQJMpyGVav4qYzyWAXuki2X\naH+rnKqEDsxzk8YzLDOAFqLGO8MwDXAYSt0lnH76dF1H3NHVUVdO0GlHdUTkas/MIzOY2DeBNZvX\n4ME7HzSeFjfiPtfqaSHCqM6cGYF2XQbW3bCuRjXo6OKDPMzCqlXClGLMQ0rvdTesww9u+4EyvUO5\nZ6n6WJTU0Wk8wyIAWoS6yMOYO3/HYKzqrLvOWpqaelVO1Q5b4Z45dXgK25/a7u/LblNcXsT5bzof\nD3/j4dDnloeRpkkhFTdO/V+VwCyv1uv612xeExggFkat4qcyakbQVhZ4903v9o1SVgnR2ef8U0Kk\n9QyLCqgFMIk8bJS+tX36tAOnlh7cMFHETsm7sR1jvrViAatDe3jMsPMnVD2FqIOwZvOalutEvNQY\n8rtL6OjqCNzGqf/rJkjXP3V4KtYcQKYqozS8hJqFiZde/8Z+bDu+DTsXd2Lb8W1KV17H1TrNmtky\nA2gBjlx7pKmdPwA8eOeDRgFoofWUTjrdOIcaDDgR7LzAmNg3kXglpThRGfILxQKoQL75mhyvHJVa\nZXSTesY1Mz0TWPIwjIrGVGWUZHbPJAhrfE7DY8kEEQAZZ3L/ZEOuZaZUTlYwf7o+WtQ7moucSiJc\nWpRQeN0l036pwqLLR1/qLmG+Mq+ccTn3RdcRhY0mb0RFY9IZ6tqThxgOhyABmrTHkgmiAso4SU6R\n556v7Wi8wV+T+yeNc5unQRLRp83AT/VWVTUAVe8SE5VBHN48capoBncNolCs726cGI40iJpyXbcv\nXSBfnMeJG5kBZJSgfCxJMH96vtrJGKW/zQBZzQ3kNzr0G61HHTXG5c0Tl4pGl9MorRiOuI3SfnUb\n3LM493E6VM8bAAAgAElEQVSc7dJUCYkAyCBGGTUTYO75ORzaeiiUK2cWyJpeOaizCcp9H9V9MhZv\nnhhdE93OBG7C3q843EmjplzX4Ve3wUuQYEhSCIgKKINEzdffDMZvGs9O528YX+PttJo1BTfd75Fr\nj/iqV/y8SpJKspZEXp04krfFdT3invGEFZSVk5VMeEXJDCCDZGoE20yVj2EwW9Xf3WBdb6fVLP9z\n0/36GfHd91k3Wo97pKojCS8V3Uynb22flQLc4LhxXY8oRnK/a6M7t6CawV6SfvdFAGQMJxtmoznF\n08QpPlNaWcL86fk643IVw1M0vRaqZGXN6kBN9+s3ojMZNSbpPtlsLxWTymVBAjqu62FachIwE/Y6\nAQrURwX7CYako4FFAGSIaq3eFu78VRW6TCKBVRinhvCZSTSrAzXdr99xZp9TZzF1jza1gwFGqJKY\nUfXmcadv8AqZkd6RUAI6LltFmBmPqbD3E6CmgiHpaGARABkiLt1/UACRFyfTY8OeR3aE7uimJZ98\nIMCV1afzNhaErhxE3pFZs4ybQfv1TdZmUzlZqabBdmomF5cXa2ZMftfAVJ0VVQ2WRPqGsAI6zMg9\nCNMZT6ODiDCCQbKBtjGhR6UEFDprb2FHV0eozt+bw6ShqmJsjWod49xdV92Fuz90t1agFJcXMXCN\nvmypX1ZFXWoJryGtWcZNv/2aVNVyt3f8pvGqUVOnLtNdCxPDYVQf/yTSN4Q1DEctlpRkG03xpotI\nw3VZBECGCP1AOUXS3YuYffPuFIoFbSlGIF4PpMW5RSzMqovROMfuubRHu70u182G2zf4HtdrXG1G\nhxG6SpcfBvKaF1nrBRU0cNCOYO1cTToPpiTsD1EEdNIdZxqVx5JCVEAZIUqULRUIi3O1ORac76rC\nFCYVhxIJPCNUi4uM9I5oV/PNdeNjU6ACYZiGqzaEoER0UdFN7ZthoHUGB1HUWb7pO1iv2kkiNiCr\nOXLctEIboyICIANEDfzSqXoqpyrYcNuGSA9sIzn5TTFNLqfLdRPk8+203/nvrZLW7ICbyPmSdBAa\nMhya1BpQGTXj1Lf7kcUcOV5aoY1REAGQAQJVBmGLvzAiJ0ZrdudvmlzOa0w2da00IS4/elVhnPJq\ny7UxtrQZBFz41gtraj53ljpROVWJnLHT1GNK57Y5tmMMo5tGczUSboRGPKXSLpIjAiADBKoMInQk\nUUa6vjVmYalkVr5qpZW3PwROXIBpAA2wNLtRnUccKpZG96ErjONUQ7vwrReGvk4OVCDLlmPHUbj3\nUzlZsewgt20InY7YWX+kd8RYtePerpWLujSro23kmmThehobgYmog4i+T0Rftb9fSET3E9EUEX2J\niLrs5cvs78fs33td+7jeXv5jInpn3CfTqpjoVKPosb0eG0GpC7R1BwjYcPsGbDu+DR/4+gcw8JGB\nUHVPeZG1BjuvMVW1X+95xKGDbnQffrO2uRfm8PgDjxsVdVHBzNhw2wYrV4zCK6hRT5yoRs1WLerS\nzHQajVyTLFzPMF5A1wJ4yPX9LwB8jpn7APwCwNX28qsB/IKZXwXgc/Z6IKLXALgCwEUA3gXgBiKK\n9obkDF2q3DhwRnpBL4Fv3QGuHZGsu2EdPjn/SezkndjJO6vpinUEdbZurw6dXcM9Ym/IVRWo0alH\nJWgGUTlZ0XpABVHuKQeqBRuZwUT1jGrVoi7N7Gj9rknQgCsL19Oo1yGi8wGsA/B5+zsBeCuAr9ir\n7ANwuf15vf0d9u+D9vrrAdzBzC8y88MAjgF4fRwn0er0b+xH5zJ/bVzlVCWyN8swDePA5gO+L4Fv\nyoKADt6vQw5rNDTxua7pwOAfL6DEJdCiJoprdAZRKBaUbp0dXR0Y3DUY2Amk4YPeLH/4ZtPMjtbv\n3EevHPWddWThepoOO0cAbMdSXaduAE8zs1NC6gSA8+zP5wF4FADs32fs9avLFdtUIaItRDRORONP\nPvlkiFNpXUxcQMs9ZQztGdKvENAH6oy7zksQ5I3jh7dDdrelsxTOzKSaDRWKhbo2VDsw3on37HtP\nKCHgtPPQ1kMY3eT/kvq100/oBQnriz98cV0QHwC87urXoX9jv38nEMMMJgqt6g/fzI5W+xwoXrek\nghTDECgAiOjdAJ5g5qPuxYpVOeA3v22WFjDvZeYBZh4455xzgpqXC0ymon1r+/xHaRE9TpyXQPcy\nlLpL1bTEI70jGKZhfKrzUxim2hGz0yFvuH0DiqWlh9pJdxBG32pNGPXf3YTNn+SO1lV56piqBnSz\nEEedMrRnSCuUi2cWMX7jeF0MBwBMHZ4CENDBczpG1zSicOOgmR2tiQ3LTRJBimEwGZ5dCuA3iGgt\ngDMAvATWjOBsIuq0R/nnA3jMXv8EgAsAnCCiTgBlAKdcyx3c27Q1JlNRp2Mor47Px9z9Euh8vi96\n30XYvWp3jX3A7fEyumkUo1eOVke8ugIYpm6XYzvG6nTnflWjwkTdugPhRnpH9O6Qhtc3yDd8+r5p\ntZDRZUfF0rPQv1FdQQsIVsk1k1b0h292IJf7mgwXhn3XdQ+00nYBBQwEADNfD+B6ACCitwD4Q2be\nSERfBvBeAHcA2AzgbnuTe+zv37Z//wYzMxHdA+BvieizAF4BoA/Ad+I9ndaktLIUmDPc6RgGdw1i\ndNNowz7m3qhgk1S9Sux2mLY/iLD6WtP9lrpL2P7UduPtdq/abdld7KLlYfzuHdbdsA49l/YsJdgz\niedwZfkc2jOUiYyReSApweUXBOit8pa2CyjQWC6gjwP4GBEdg6Xjv9lefjOAbnv5xwBcBwDM/CCA\nOwH8CMDfA/goM0dzk8gRk/sn8eIzLwau54wc+jf2+3Yipobi+cp83TKvYXDq8FRseYFM9a1h9bVG\n+yVLQLlVVkHbVU5WALb+O5+juA/WJNgzFNruziBtFYEQDp1NoNRdqrl3WXABBQBizm7u+YGBAR4f\nH0+7GU1FF5TjxptjXxvIY6d1dghK7+xd38twYTi2imAbblcHLnmnwapZh6rGgHv7UDMiexRe6i7h\n9NOnI0U+B103Lyb3OI7jCNnARLWjfbcI2Lm4s+E2ENFRZtan2rWRSOCU8VVFEEKVn1N5yvRv7Nc+\nbCauhnHYGxxDshfVNHj8xnEUz7S8aFRqF9XLFTZNBhCssvIjrPtg1GuYdf96QY2JuskvBYqqSFCz\nkHTQKaNVbawuG0fPBqkGoqpPGg64giWYdO6rOgPu3PNzmK/MV2sFjG4axUjvCA5tPaQMZmtWtk8d\nXkOeXxxBNb2GDx1nqOMhs+5fL0RH927xAscWpWyCqIBSRpUJ1E/lkfQxJvdP4sDmA0aqkq4VXZh9\nbrYuDbN3JG9cecxrNNUYUUvdwUb0uHBfN5Pr6qf+cQzxgDrLp+j7843fu9Wo+k9UQC1CErnGGzlG\n/8Z+S8duQKm7hOufvR6A3sth+r7pYM8iB+97oZFBTpR0s4UAFcjYkGeSuM7tlQSgxu0zbACdEJ20\n3DH93q2k1H/ylLUJjbjBmdoC3A+trnM8uvdo7CmnnZdWm/M+bDptDcxccw1NXFN1Lr4qX363Z5YT\nQAdkP9NmK5O2O2YSRXf8EBtAyoTNVBg1d00j9K3tC9RjA2aFXow7f93xPMsd47dfZO6G2/xLSJri\nxAQ4BNlWdC6+Tr4f973U5Wo68IEDid7rdiNtd8y000HIDCAl/PTg3iRtOhfJJEYrk/snMbFvom4E\nXegsYHF+KZVBmEIvqoyfpe4SulZ0BbqDrtm8BlOHp5TTde8sx7nGfuUjwzD77GyNh0bf2j6M31hv\no6qcrGC4MGydq0LgdZ3VBaBW768TjH51EbIQSdrqpJ2RM+1yk2IETgHTEpB1dX01qoxm+ovrjJje\nDtv70KrOsVAsgBe5rrPr6OrA+lvWK0s/mr4YJvEEdZBZFLYb97WO6t/vuPc2EhuQhPNAO2AaU9Nq\niBE4w5jkr6EOql/HsJRfnOj2XTlVqTNiulGNbGafm1V2tl1ndSk7LVO7hTKewKQkI0OZbsEP53pM\n7p+M7N9f7ilHvmfOMU0M0EIwSdU9zioiAGLGb9Rq6v5YN/IPoJkGI90I2asPV+HtwHWJsiqnGvPe\nUQpUg4lteXW52j5TV9dyT7kqcKLgpLY2coNV4Ng2oqouRG1US9IqmKxdfxEAMeLnUQDU+3rr6Cx1\nWoW/VaoJjxqolUYrzfJ4iDKadl83U1dXZ5swGUi9OKmtVSPPQrEAIvKtJOYIqSjXMm2Pl6ySVKK4\nLF5/8QKKEb9peZhOo3KyghefebGupmxxeRED1wwkmhxMNzqPMmpvlseDttPzehLZ31XXLUgIubdp\nROXmTm3tjuYudZew7CXLrM7fx+PK8XKKci3T9nhpd7J4/WUGECPaabmTCjgEi3OLgYbWJIhz1N6s\n6bZOj+vnMaTah85bqNRdqjEINpojyZ3zXxlRrNNEuSqBRbmWaXu8tDsm1z9pFZEIgBjRdgxk6/V9\nCoGoCDK0JkHcRrJmTLdNOsOqS+imUZR7ylj5qpU4/q3j4AUGdRAu2XKJdv9OKulQHkY+eIWn8ezQ\nUwks7LVMO+io3Qm6/mmoiEQFFCODuwa1hS9V+feDyMKLmYWydSZ4axmoXFLdwXYPjz1c1afzAmP8\nxnF0rehS75xQs+34TeOYe2GuapAtdZfq1HU6vMIzjDdRo5XA0g46aneCrn8aKiKZAcRI/8Z+rRpB\nFfzkR5ZezFYsA+jGdIQ9+/ysWeyF/Z0XuCbbqbbyl6sGAWBlNx3bMVadSZgQx/OQdtBRuxN0/dNQ\n0YkAMCCMXk5Xs9fJkGmCt1xju6IK7jLV6ddsb6qvZ6sCl/uYQds6IzTHRuAcz7nf5dXlascdJlah\nUCxg2UuWRSpF6UerC/NWx+/6p6GiEwEQQFi9nJ9BUqc3dtIjOJ2FvKD6YjEOQffBNNpahdvgaxLt\nOzM9U3c8Z3bg3M+R3pFQsQqX33q5PAdtRhpBaWIDCCCsXk6nM193w7qaZGVuWwEv1nYWgpnaxu8+\nRPXV9+7PpChOuacc+JyEmca7A9TSII2Eg0I69jaZAQQQRS+nm+b5RZ1KGH8tph1mlPvjVzvAu12N\n3lah33cEd1Bed9OcQ2nbfrIYrNROJK2iEwEQQFi9XFAqiINbDmptAeKPvYSpr71fSmbV9sUzi75B\nbKWVparax6vHr6lm5rm/OluDkf7WFirl1Zadw+2umvSsUHIMpU+SsQAiAAIIo5dTjZ5GrxzFkWuP\nYGjPUKBaIgtun83G9OH2LfBi4zda1qVa8IvFKBQLmH12KWGdI6i9o+Awth+nfb6R02w5CXgNw2mM\nviVYLF2SnoGJDSCAMHo5XQfvVHfyG9GmPfVPgjDFb1TXfeAj6jQYKp21avtlL1nm275qKgYFcy/M\n4cDmA1p9eNBzEiTcq7NCz+Qw6VQBQUVuhOaSdCyA1AOIkeHCsK9nh84VlDoI79n3Hq03S178tpuR\nez1MXny/+2NaUzhqzv1GvJJAwM7FneG3i4DUGUgX7TMa8hkwrQcgM4AYMRnlqSIB/Tr/MOUis04z\n1AthRkx+92f22Vmj40UdjTkzBCcYLAxJjr5bJfI7ryQ9AxMBECNBLoPOy2T6cmUxe2AjNOPhDiNU\n+tb2KdftOKPDNwWz6TGD6N/Yj+1PbceG2zdUnwEnnYSONFSDfmk1hOaSdLoOMQIHEEYF4yw/+NsH\nlcbG2eesUaapuiNvBrlmBLqE8dKaOjyl3MfCafPOH7AC94YLwzXPQ9jnxOsZpko/IYGB7UfS6TrE\nBuBDGH1oTdoBTe1eAAABF771Qpw6dirwBuexXqlpR6laD1h6MZyKZJWTFaVvflgbgIrimXZeIJ9t\ndFHeYVI55MnOI1j388i1R6o2pTRSu5jaAEQA+KDrgKnDTt3Qo87zEhY/odJOBjk/IRpYLctg1OxX\n4H6+Mh+6OlcY8nzfhCUm90/irqvuwuLcYs3yjq4OrL9lfWL3X4zAMaBTtfAC1xhlj1x7JHLnD+j1\n+u1kkKsxeAN1o+7FuUX/zpiXZkZ+RV9U+tWhPUNKl9G4On+gtW03gjljO8bqOn9gqRJc1hAbgA+m\n2SAb6fwddMKmXbI3NlJn1yHINhKkXzUpYN/M9gmtj989zuL9FwHgg0k0aly0e6BNHC+HyTU0FaiN\nln3U7VPIN37PTRbvv6iAfPCqYHQue6XuUr37Z4gawO0QBRxE0MtRKBZ8q27FfQ1NsoCGQe5xe6Bz\nNS50FjJ5/2UGEECQy567IpTb8l9cXgzWW8MSKm79cDuoe1QoZ1sewy6g8AKKuWCKg7Mv9z2Nisow\nLZ4/+UTnarysvCyT91cEQADeF3XN5jVWVSo7W6STI6YuvbNhAXhdwrF2w9T/Oclr42T5bEQAUAfV\nuexKyuX8olNl+iYDtEljUCACwAfVizqxb6LO79u01GMQ7Z52N4sG70ZtE5dsuaRumaRczi9Ryzqm\nNSgQG4APuhf16N6jTTMMZ9FToJ1pxHA38JEBrLthXd3yvEV4C0tETeWQVtqXQAFARBcQ0TeJ6CEi\nepCIrrWXrySie4loyv7/Uns5EdFfEtExIvoBEV3s2tdme/0pItrcvNMyI6j0nW8cQJNwdNt5pdXK\nDape6CCDNGCpfsZvGleeo6Rczi9RY3fSGhSYqIDmAfwBM3+PiM4CcJSI7gXwQQBjzPwZIroOwHUA\nPg5gCECf/fcGADcCeAMRrQSwE8AArDCfo0R0DzP/Iu6TMsFkytUMV0DA6hw6z+g0thPkhVbUfats\nE31r+/DgnQ/62gb8bDtpFP8WkiOKKjOq6qhRAmcAzPwzZv6e/flZAA8BOA/AegD77NX2Abjc/rwe\nwBfY4l8AnE1E5wJ4J4B7mfmU3enfC+BdsZ6NAc4IdPTK0cApV9/avlDunKbwImtVSCbGolalVbOb\nurNjDu4axMS+iZrOv1AsWGmeNa7C3nNspwhvwYyks4A6hDICE1EvgNcBuB/Ay5n5Z4AlJIjoZfZq\n5wF41LXZCXuZbrn3GFsAbAGAnp6eMM0LxKQohzPlmtw/iYl9E6GSh5niSPU0JH6a5EH3rRJii3OL\n6FrRhe1PbddGEKuKzUuHLzgknQXUwVgAENEKAH8HYBszP0OkHRqrfmCf5bULmPcC2AtYyeBM22eC\nSboBpwOOIzWBio6uDm0CubyrAXTT3CTsHnG52AUJsTim8hIj0J6kMSgwEgBEVITV+e9n5lF78c+J\n6Fx79H8ugCfs5ScAXODa/HwAj9nL3+JZ/q3oTQ9P0EjT3QE3Q/cPWOoCdzBTZ6mzacFMWWNw16Ay\nU+Lss7PVOr7NIE7bQ1AH36h+vxXtJELjuDPhOqVjk6gHYeIFRABuBvAQM3/W9dM9ABxPns0A7nYt\n/4DtDfRGADO2quhrAN5BRC+1PYbeYS9LDL9RmKOHBay0wQ2jmSDNPT9XLfFYOVnBfGUeG27b0BaV\nl/o39isLszc7U2KctocgXW2j+v1WtZMI0Tm09RBGN41WBxZeB4JmesqZzAAuBbAJwCQRPWAv+yMA\nnwFwJxFdDWAawG/avx0GsBbAMQAvALgKAJj5FBH9KYDv2ut9iplPxXIWhuhGZ84LemjrIYzfNN6w\n3r/UXULXii6jWYQ7AKgdpv46I3cz7QBx2h5MdLWNTOXzYCcRzJncP+nb5zQ7QDBQADDzP0PvC1M3\nr2WrwsxHNfu6BcAtYRoYJ/0b+zF93zSO7j0KXmBQB2HN5jXVzjeOzr9QLFRzA6nUHSpmpmfaZuqf\nhrtb3Mdspq42LXdAIR3GdowF9jnNFP65jQSe3D+J3at2Y5iGMUzD2L1qNw5tPYSJfRPVKRYvMCb2\nTVRH3o12/tRBuPzWy6sdhErdoaLcU26bqX8a7m66zJ6zz81mLhAtLXdAIR1MOvdmCv9cCoDJ/ZM4\nsPlAja925WQF4zeOKzvZI9ceicXoy4tcMzI08el3Xu52mfqn4QPvHLPUXettVDlZabqONSwSI9Be\nBHXuzRb+uUwGd+TaI6HSNTSa7tfBezODIompg6ovd7UWbsA+80Aa7m66zJ7OACDp9vjZeyRGoH3w\nKzqVhBdQLgVAXB16GFSSenDXIEY3jWpVS7zAVRWPpAdoPtpUvScrTXVD9dIu9h4hmLQCwBzIstlm\nk4GBAR4fHw+93TDFX8/Vj1J3CUN7hpQ3zaQtjicSkN6D0A6M9I7oy/XZBeXTbEeSbRDyDREdZeaB\noPVyOQModZcSnQXMV+a1v5VXmxWWH9sx1haxAGkyuGsQo1eOKn9L0tbSLvYeIfvk0gh80fsuSvR4\nft46prVl5eVvPv0b++sMwQ4mBTviSmMt6aAFHUmnS8+dAKgmcUsYXQduWlheXv5kGNozFNrN0tHZ\nOxHcQRGaQS+xuHoKKsI+Z3GQOwHQrCRuQfh14O50wu/Z9x55+VMkiptlmBgNk5dYXD0FFWnEAuXO\nBhCXKqWazsGgCEiYDjxtq78Q3s0yjM7etN6vuHoKXtKwDeVOAMRRxau4vKj06nHquzaas0de/tYi\nTBprMfAKUUkjDUjuBIBfYIUp57/p/LoOuh0StTWDPFy3MGmsJZdPfmn2s5xGLFDubABe/WoUHh57\nuEZnm4ZxJg/k5bqFSWMtBt58ksSznIZtKHcCAKg1ukbF/WK3S6K2uMnLdZvcP6mNK1GVesyqgTdp\nF8M80exnuVqrfJMVp5JUjZDcqYCA2qmaU10nLDOPzFSn96LXjUYerpsz8tOhUu1k0cYj6Scao5nP\ncpr3JnczAO9ULUrn7+BM8SRwJxp5uG5+bsWtpNrJy2wsLZr5LKd5b3InAOKMA3Buguh1o5GH6+Y3\nwsuKaseEPMzG0qSZz7LOa7FZdcnd5E4AxP1Az0zPZFqvm2XycN20I7/V5XycRwvNxtKkmc+yLjuA\nbnmc5M4GEEccgHd/QPP0unlwk/Qji/rwMOQlTXdeziNNmvUs69TUjaivTcndDKBvbV+k7aiD0NHV\nUbOs2S9IXtwk84yqmlhnqfXGTXmYjeWV8mr9LLPZtN6THMDU4SmzFQnVQi1OPn8g2RQNpmkDhOYT\nNBNzp/x2SkkCreVB0+qzsbyS5uwsdwIgjA1AVXItyRdEDHPZIMgNTwS10EzSzA+WOwFgbAPg+Pxt\no+rxJW1AfDRiSwnq4EVQC80mrdlZ7mwApgVYHBrxt53cP4ndq3Zj9MrRSHr8PLhJZoFGbSlBHbx4\n0Ah5JXcCwGvsKnWXLAOej0dVlJGc0+moUgSYChUxzMVDo4E0QR28CGohr+ROBQTop1PaouBs/dao\n2sCNqVARw1zjNKqiCTLCSQ0HIa/kUgDo8EsVHdYeENS5iHogORq1pZh08CKohWaTRkxQWwmAmhdd\n0WGE8ezwMzaLeiBZ4nCjkw5eSJO0EsLlzgYQhJMqWodpFLHO2FzqLokeP2HEliK0OmklhGurGYAb\nXZpo0/wbohfOFjKCF1qZtFyN21YAxJF/QzodQRDiIK2YoLZTATmkmX9DEATBTVquxm0rAMS3WxCE\nrJCWHattVUCiwxcEIUukoVJuWwEAiA5fEIT2pm1VQIIgCO1O4jMAInoXgD0AOgB8npk/k3QbBEEQ\nwpLH6n2JCgAi6gDwVwDeDuAEgO8S0T3M/KMk2yEIghCGtCJ1m03SKqDXAzjGzD9l5lkAdwBYn3Ab\nBEEQQpFWpG6zSVoAnAfgUdf3E/ayKkS0hYjGiWj8ySefTLRxgiAIKvJaFChpAaDKs1ATesvMe5l5\ngJkHzjnnnISaJQiCoCevRYGSFgAnAFzg+n4+gMcSboMgCEIo8ho4mrQA+C6APiK6kIi6AFwB4J6E\n2yAIghCKvGacTdQLiJnnieh3AHwNlhvoLcz8YJJtEARBiEIeA0cTjwNg5sMADid9XEEQBKEWiQQW\nBEFoU0QACIIgtCkiAARBENoUEQCCIAhtCjGbl0BMGiJ6EsAjDexiFYCnYmpOs2iFNgLSzjhphTYC\n0s44SbqNq5k5MJI20wKgUYhonJkH0m6HH63QRkDaGSet0EZA2hknWW2jqIAEQRDaFBEAgiAIbUre\nBcDetBtgQCu0EZB2xkkrtBGQdsZJJtuYaxuAIAiCoCfvMwBBEARBgwgAQRCENiWXAoCI3kVEPyai\nY0R0XcptuYWIniCiH7qWrSSie4loyv7/Uns5EdFf2u3+ARFdnFAbLyCibxLRQ0T0IBFdm9F2nkFE\n3yGiCbudw/byC4nofrudX7JTjYOIltnfj9m/9ybRTvvYHUT0fSL6aobbeJyIJonoASIat5dl6p7b\nxz6biL5CRP9qP6Nvylo7iejV9nV0/p4hom1Za2cdzJyrP1hppn8C4JUAugBMAHhNiu15M4CLAfzQ\ntWw3gOvsz9cB+Av781oAR2BVTnsjgPsTauO5AC62P58F4N8AvCaD7SQAK+zPRQD328e/E8AV9vKb\nAHzE/rwVwE325ysAfCnB+/4xAH8L4Kv29yy28TiAVZ5lmbrn9rH3Afiw/bkLwNlZbKervR0AHgew\nOsvtZOZcCoA3Afia6/v1AK5PuU29HgHwYwDn2p/PBfBj+/NfA/gt1XoJt/duAG/PcjsBLAfwPQBv\ngBVh2em9/7DqTrzJ/txpr0cJtO18AGMA3grgq/ZLnqk22sdTCYBM3XMALwHwsPeaZK2dnra9A8B9\nWW8nM+dSBRRYeD4DvJyZfwYA9v+X2ctTb7utgngdrNF15tppq1YeAPAEgHthzfaeZuZ5RVuq7bR/\nnwHQnUAzRwBsB7Bof+/OYBsBqx73PxDRUSLaYi/L2j1/JYAnAdxqq9Q+T0RnZrCdbq4A8EX7c5bb\nmUsBEFh4PsOk2nYiWgHg7wBsY+Zn/FZVLEukncy8wMyvhTXKfj2AX/FpS+LtJKJ3A3iCmY+6F/u0\nI817fikzXwxgCMBHiejNPuum1c5OWCrUG5n5dQCeh6VK0ZH2O9QF4DcAfDloVcWyxPupPAqAVig8\n/y8InL8AAAHDSURBVHMiOhcA7P9P2MtTazsRFWF1/vuZeTSr7XRg5qcBfAuW/vRsInKq27nbUm2n\n/XsZwKkmN+1SAL9BRMcB3AFLDTSSsTYCAJj5Mfv/EwAOwBKoWbvnJwCcYOb77e9fgSUQstZOhyEA\n32Pmn9vfs9pOAPkUAK1QeP4eAJvtz5th6dyd5R+wPQTeCGDGmT42EyIiADcDeIiZP5vhdp5DRGfb\nn0sA3gbgIQDfBPBeTTud9r8XwDfYVrg2C2a+npnPZ+ZeWM/eN5h5Y5baCABEdCYRneV8hqW3/iEy\nds+Z+XEAjxLRq+1FgwB+lLV2uvgtLKl/nPZksZ0WSRsdEjLCrIXlyfITADtSbssXAfwMwBwsqX81\nLB3vGIAp+/9Ke10C8Fd2uycBDCTUxl+HNf38AYAH7L+1GWznrwH4vt3OHwL4pL38lQC+A+AYrKn3\nMnv5Gfb3Y/bvr0z43r8FS15AmWqj3Z4J++9B5z3J2j23j/1aAOP2fb8LwEsz2s7lAE4CKLuWZa6d\n7j9JBSEIgtCm5FEFJAiCIBggAkAQBKFNEQEgCILQpogAEARBaFNEAAiCILQpIgAEQRDaFBEAgiAI\nbcr/Bw1EbIWHHgM8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5012a2cf90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 单个特征散点图\n",
    "plt.scatter(range(data.shape[0]), data[\"cnt\"].values,color='purple')\n",
    "plt.title(\"Distribution of cnt\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##去掉离群点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Jes6MJy8CQGwAgpBjVK6gKtWPn6rIvZ0fc8/PWcKG1W6mDo6wca87fuN40+ILTAu3mK6X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\nbcr/Bw1EbIWHHgM8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5012d82590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "#data = data[data.cnt < 8000]\n",
    "#data = data[data.cnt > 500]\n",
    "plt.scatter(range(data.shape[0]), data[\"cnt\"].values,color='purple')\n",
    "plt.title(\"Distribution of cnt\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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R08Sf3t/ndzgSpZRARICm1g7WVtQye1JGzNx53p8LZ+ZSlJvKva/vQBc0SiSUQESANbtq\naOtwLJqW5XcowyYQML5x/gl8sL+BFzfu9zsciUKj418tGVY9zS11zPULJg9jJOHp6HS8U1bNlKwx\n5Gck+x3OsPrM7Inc+/oOfvLSVj41azxxQf1PKeHTp0VGvff3HObw0TbOKRp9U98EA8Y/XzyTskON\nPFWiK7JkYJRAZFRzzvHmtkPkpiXG/KW7vbnopFyKp4zjv17eRlOr7guR8CmByKj2+tYq9tc3c05R\nTsxfutsbM+O7l8zkYEMLD7xV5nc4EkU0BiKj2r1v7CA9OZ7TJqX7HYqvzijM5NOn5XH3a6VcPjuf\nqdmDNwtxX2NiMDLHxSQ86oHIqLWyrJpVO2s4c3o2cQH9KvzrZbNIDAb4/nPv67JeCYt+a2RUcs7x\nk79sJTctkfkxPO/VQOSOTeI7l8xkeWk1v1+7x+9wJAoogcio9Ma2KlaX1/KtC4tIiNOvwTFfmD+Z\nuZMz+OHzm9lzuMnvcGSE02+OjDrHeh+TMpO5pnhS/xuMIoGA8dPPz6G9w/GNx9+jtV3zZEnvlEBk\n1Hlx43427qnnHy86Ub2PHkzNTuE/rzqN9RWH+fcXtvgdjoxg+u2RUeVoazs//tMWZk5IY8mciX6H\nM2JdcmoeN501lUfeKefxlbv8DkdGKF3GK6PKz18tZc/hJp7+20UEA6Pzvo9w3XbJTMqqjvC9328k\nIRjgap3uk27UA5FRo/RgAw++VcZV8wo4Q1de9Ss+GODev5nH2UXZfOd3G3iqpMLvkGSEUQ9EhpVf\nN5V1djq+/9xGkuOD3HbJzCF5j2gw0Ikuk+KD3P/FYr762Gq+88wGnimp5NOn5RHfbdJF3Qw4OqkH\nIqPCfW/uYEVZDd/79Elkpyb6HU5USU4I8uiX53NOUTarymu4740dlFUd8TssGQHUA5GYt2ZXLT/9\nyzY+fVoen9d5/IjEBQMsPiWPKVkp/GHdHh58eyfTc1JZOC2L6bmpfocnPlECkZh2+Ggrtz6xlrz0\nJP7PZ0/FRumEiYPlpLyxTM9NZeXOGt7YepDfrNxFfNB45YMDnJCTSmHWGFKT4kmMC9DpHC3tnawo\nq6a9o5P2TocRmkI+KT5Idmoi2WnqDUYzJRCJWY0t7Xz5kdVUNbTw5NcXMjYp3u+QYkJ8MMBZ07NZ\nNC2LnYca2bS3juojrazZVcHRCKaDf+H9fVx2Wh5XnD5RpxejjBKIxKSW9g5u/nUJGyrruOf6uZw+\neZzfIcWcYMCYnpvK9NxUrl8wGecc1Y2tNLV20NzWgZmRFB/gTxv2ER8MEBcwHKEnQDa2tHPoSCt7\n65rYe7iJH/1pCz97eTt/f1ERN36i8GOD9DIyKYFIzKk72sa3lq5leWk1P716NotPmeB3SKOCmfXY\ng0jr1vOLD4au7spKDT3E6/oFk9l2oIF/f2ELP/rTFp4uqeTBG4uZlDlmuEKXCCnNS0zZvLeey+9+\nm3d3HOKOz53K5+YV+B2ShOHE8Wk8/KUzeOCGYvbXN3PlL95h4546v8OSfiiBSEyobWzlx3/azBW/\nWE5LewdPfn0R15yhexOiiZnxyVnj+d3fLSIxLsA1v3yXnYca/Q5L+qBTWBK1Wto7WFFWw1827WfZ\nur00trbz2bkFfHfxTHJ0dU/Ump6bxrPf+ATXPbCCx1fu4pvnTWdcSoLfYUkPlEBkxGhsaWdFWTW7\na45ysL6ZlvZOWto7aW3vpKW948PvG1va2V19lN01R2nvdIxJCHLhSeP51gXTOXF8mt+7IYNg/Ngk\nHryhmEvveovfrNzF1885QTMnj0BKIOKrhuY2VpfXsHV/A5W1TXR9kGrAIDEuSEJcgMS4wIdfkxOC\nzMxLY/EpE5g7eRxnFWWTFB/0bR9kaEzLSeXaMybz6DvlPLu2kmt1SnLEUQIRXzQ0t/HmtipW7qyh\no9NRMC6ZC07K5cZFhUzJGsOE9CQSggHd+DfKnTg+jQtPyuXlLQeZXVDPSXlj/Q5JulACkWG3dX8D\nT6+poLmtgzmTxnH+jByyvMs/K2ubqKzt+VGqmrBvdDr3xFze31PHsvV7mZaTQmKcepsjhU4qyrDp\ndI4/b9zHo++WMzYpnm9dUMRV8wo+TB4iPQkGjCvnTKSuqY2XNx/wOxzpQj0QGRadzvHc2j2U7Krl\njMJMLuthSnCR3kzOSmH+1Eze2VHN3CnjyEtP9jskQT0QGQZdk8f5M3K4Yk6+kocM2MWzJpAYH+Cv\n6oWMGGH1QMxsMfAzIAg86Jz7j27rE4HHgHlANXCNc67cW3c7cBPQAdzqnHuprzbN7BbgH4ATgBzn\n3CGv3Lz6lwJHgS85596LeM9l2Pxl04EPk8dFJ42PeGB8oA9DkoHp72FfQ7VtuJITgpxdlMNfNx+g\nouYokzLH6DPhs37/DTSzIHAPcAkwC7jOzGZ1q3YTUOucmw7cCdzhbTsLuBY4GVgM/MLMgv20uRy4\nCNjV7T0uAYq8183AvQPbVfHDxj11vLm9ivmFmceVPEQAPjEtizEJQV7eol7ISBDOeYT5QKlzrsw5\n1wosBZZ0q7MEeNRbfga40OsxLAGWOudanHM7gVKvvV7bdM6tPdZ76eE9HnMhK4AMM8sbyM7K8DrY\n0Mwz71UyaVwyl52Wp+Qhxy0xPsi5J+aw/eARTXMyAoSTQCYCFV2+r/TKeqzjnGsH6oCsPrYNp81I\n4sDMbjazEjMrqaqq6qdJGSrtHZ08sWo38QHj+gVTiNOYhwySBVOzSE2M4/WtB/0OZdQLZwykp38b\nXZh1eivv6a9J9zYjiQPn3P3A/QDFxcX9tSlD5PVtVRyob+HGRVNITx76Bzn1dw5e58NjR0JcgEUn\nZPHXzQc4UN/M+LFJfoc0aoXzb2El0PVB0gXA3t7qmFkckA7U9LFtOG1GEoeMAPvrmnljaxVzJmUw\nY4LuHJbBN78wk7iA8c6Oar9DGdXCSSCrgSIzm2pmCYQGxZd1q7MMuNFbvgp41TnnvPJrzSzRzKYS\nGgBfFWab3S0DbrCQhUCdc25fGPHLMOrodDy7tpLE+ACfPlVDVDI0UhLjOH1yBmt319LY0u53OKNW\nvwnEG9O4BXgJ2AI85ZzbZGY/NLPPeNUeArLMrBT4NnCbt+0m4ClgM/Bn4JvOuY7e2gQws1vNrJJQ\nD2ODmT3ovccLQBmhgfgHgG8c997LoFu6ejeVtU1cflo+KYm6T1WGzidOyKa907G6vMbvUEYtC3UU\nYlNxcbErKSnxO4xRo6G5jfN/8jqpiXF87expuupKwtLX+FR/Y1sPL9/J/vpmvnPxTIKBj37eNO4V\nOTNb45wr7q+eLo2RQXPfGzs4dKSVS0/VJbsyPBZNy6KhuZ2t++v9DmVUUgKRQbH3cBMPvrWTJXPy\nKRg3xu9wZJQoGp/G2KQ4VpfX+h3KqKQEIoPip3/ZhgP++eIZfocio0gwYMydMo5tBxqoa2rzO5xR\nRwlEjlv5oUaeW7eHLy6cot6HDLviKZk4YM0u9UKGmy6TkeN292ulxAWMr587ze9QJAod70SMmSkJ\nnJCTwppdNZw3I4eAxt+GjXogclx2VTfy+7V7+MKCKeSm6Y5g8UdxYSa1R9vYUXXE71BGFSUQOS53\nvxrqffyteh/io1l5Y0mKD7B292G/QxlVlEAkYpW1R3l27R6umz+ZXM1HJD6KDwY4dWIGm/bW0dLe\n4Xc4o4bGQKRH4UxO+Ku3yzHg5nPU+xD/zZmUweryGrbsq2fOpHF+hzMqqAciEak72sbS1bu5fHY+\n+Rl6PrX4b0rWGDLGxLOuQqexhosSiETkNyt3cbS1g6+drd6HjAwBM+ZMymD7gSM0NOuekOGgBCID\n1t7RySPvlHN2UTaz8jVdu4wccwoycMCGyjq/QxkVlEBkwNZVHKaqoYWvn3OC36GIfETu2CQmZiTr\nNNYwUQKRAXHO8c6OamZOSOPM6Vl+hyPyMbML0tlzuIlyPTN9yCmByIDsrG5kf30zXz6zUDPuyoh0\nakEGAM9v0ANLh5oSiAzIuzuqSY4PsmTORL9DEelRenI8hVlj+ON6PbB0qCmBSNhqG1vZvLee+VMz\nSYoP+h2OSK9OLchg64EGtu5v8DuUmKYEImFbsbMaM1gwNdPvUET6dEr+WAKm01hDTQlEwtLW0UlJ\neS2z8saSMSbB73BE+pSWFM8nTsjmj+v3EsuP7fabEoiEZUNlHU1tHSycpiuvJDpcPjuP8uqjbNyj\nx90OFc2FJWFZubOanLREpmanAMf/DAeRoXbxyRP4/nMb+eOGvZxakO53ODFJPRDp157aJiprm1gw\nNVOX7krUyBiTwDlFOTy/fi+dnTqNNRSUQKRfK3dWEx80TtcMpxJlLpudx966Zt7brcfdDgUlEOlT\nU2sH6ysPM7sgg+QEXbor0eWik8aTGBfg+Q26J2QoKIFIn9ZW1NLW4VigwXOJQmlJ8VwwM5fnN+yj\nQ6exBp0SiPTKOcfKshomjUtmop75IVHq8tn5HDrSwsqyar9DiTlKINKrskONVB1pYcFU9T4kep0/\nI5eUhCB/1E2Fg04JRHq1siw075UugZRolpwQ5JOzxvPixv20tnf6HU5MUQKRHtU3t7F5Xz3zpowj\nPqiPiUS3y2fnc/hoG8tLD/kdSkzRXwbpUUl5DZ0O5mveK4kBZxflMDYpjj+u12mswaQEIh/T3tHJ\nqp01FOWmkp2a6Hc4IsctIS7A4lMm8JfNB2hu6/A7nJihBCIf88oHB6lvbtesuxJTLp+dz5GWdl7f\netDvUGKGEoh8zG9W7CI9OZ4ZE8b6HYrIoFk0LYuslAT+qJsKB40SiHzEzkONvLX9EGcUjiMY0LxX\nEjviggEuPTWPV7YcoLGl3e9wYoISiHzEb1fuIi5gFBfq9JXEnstn59Pc1snLWw74HUpMCCuBmNli\nM9tqZqVmdlsP6xPN7Elv/UozK+yy7navfKuZXdxfm2Y21Wtju9dmglf+JTOrMrN13uurx7Pj8nHN\nbR08vaaSi0+ewNikeL/DERl0xVPGMWFskp6XPkj6TSBmFgTuAS4BZgHXmdmsbtVuAmqdc9OBO4E7\nvG1nAdcCJwOLgV+YWbCfNu8A7nTOFQG1XtvHPOmcm+O9Hoxoj6VXf1i3h8NH2/ibhVP8DkVkSAQC\nxqdPy+ONbQepO9rmdzhRL5weyHyg1DlX5pxrBZYCS7rVWQI86i0/A1xooQdHLAGWOudanHM7gVKv\nvR7b9La5wGsDr80rIt89CZdzjoeXlzNzQhoLp+n0lcSuy2fn09bheGnzfr9DiXrhJJCJQEWX7yu9\nsh7rOOfagTogq49teyvPAg57bfT0Xp8zsw1m9oyZTQojdgnTyp01fLC/gS+fWaiHRklMm12QzqTM\nZN1UOAjCSSA9/TXpPi9yb3UGqxzgj0Chc+404GX+u8fz0UDMbjazEjMrqaqq6qmK9OCR5eVkjIln\nyZzu/xuIxBYz4/LT8nlnRzWHjrT4HU5UCyeBVAJd/9svALqn7g/rmFkckA7U9LFtb+WHgAyvjY+8\nl3Ou2jl37Gg/AMzrKVjn3P3OuWLnXHFOTk4YuyeVtUf5y+b9XDd/MknxemiUxL7LZ+fT0el44X0N\nph+PcBLIaqDIuzoqgdCg+LJudZYBN3rLVwGvOuecV36td5XWVKAIWNVbm942r3lt4LX5BwAzy+vy\nfp8BtgxsV6U3v16xCzPT4LmMGjMnpDFzQhq/W1PpdyhRrd8E4o1H3AK8ROiP9lPOuU1m9kMz+4xX\n7SEgy8xKgW8Dt3nbbgKeAjYDfwa+6Zzr6K1Nr63vAt/22sry2ga41cw2mdl64FbgS8e36wKhR9Yu\nXVXBp2aN10OjZNQwM66aV8D6yjq2HWjwO5yoZaF/+mNTcXGxKykp8TuMEe2JVbu5/dn3efLmhR95\nbO1vV+72MSqR43f9gsl9rj90pIWF//4KN501ldsvPWmYoooOZrbGOVfcXz3diT6KOed4ZHk5J+WN\n1bTtMupkpyZy3oxcnl27h/YOPWgqEkogo9i7ZdVsPdDAlz+hS3dldLpqXgFVDS28tV0PmopEXP9V\nJFb96PktjEkI0tTWoVNWMipdMDOXcWPieXpNBefPzPU7nKijHsgotaPqCFv21TO/MFOPrJVRKyEu\nwJWnF/Bpj3O8AAAPLklEQVTXzQeoatA9IQOlvxyj1ANvlhEMGItOyOq/skgMu37BZNo6HE+VVPRf\nWT5CCWQUOljfzLPv7WHulHGkadZdGeWm56ayaFoWT6zaTUdn7F6VOhQ0BjIKPbR8J+2dnZw9Pdvv\nUESGTF/jet0v8f3Cwsnc8tu1vLmtSmMhA6AeyChT39zGb1fs5pJT88hKTfQ7HJER4VOzJpCdmsjj\nK3f5HUpUUQIZZR5ZXk5DSzt/d+4JfociMmIkxAW45owCXv3gIJW1R/0OJ2oogYwi9c1tPPhWGRed\nNJ5TJqb7HY7IiPKFBVMwMx5ZXu53KFFDYyCjyMNvl1Pf3M4/XFTkdygivuptfOSU/LE8tmIX37qw\niPRkXWDSH/VARom6pjYeelu9D5G+nFWUQ2t7J0tX6cbacCiBjBIPL9+p3odIPyZmJDMtJ4WHl5fT\n2q75sfqjBDIKVDW08MCbZVx8snofIv05e3oO++ub9cjbMCiBjAI/e2UbLe2dfHfxTL9DERnxThyf\nyswJadzzeqlm6e2HEkiM21F1hCdWVXD9gslMy0n1OxyREc/M+IeLiiirauQP69QL6YsSSIy748UP\nSI4PcuuFGvsQCdfFJ0/g5Pyx/OyV7bSpF9IrJZAY9tb2Kv6y+QB/d94JZOuuc5GwmRn/9KkT2V1z\nlGf03PReKYHEqOa2Dv7luY1MzU7hq2dP9Tsckahz/oxc5kzK4OevbKe5rcPvcEYkJZAY9cs3yiiv\nPsq/LTmFxLig3+GIRB0z4/ZLZrK3rpn73tjhdzgjkhJIDCo/1Mg9r5dy+ex8zirSjLsikVowLYvL\nZ+dz7+s7qKjRHFndKYHEmI5Oxz89vZ7EuAD/8umT/A5HJOr9z0tnEgwY//b8Zr9DGXGUQGLMfW/s\nYM2uWn50xSnkjk3yOxyRqJeXnswtF0znL5sP8NoHB/0OZ0RRAokhG/fUcedft3HZaXl8Zna+3+GI\nxIybzprKieNT+e7vNlDb2Op3OCOGEkiMqG9u49Yn1pKVmsCPrjgFM/M7JJGYkRgX5M5r5lB7tJX/\n+fv3cU6PvgUlkJjQ2en4x6Xr2F1zlLuuPZ2MMQl+hyQSc07OT+fbn5zBixv38+x7e/wOZ0RQAokB\n//XKdl754CD/ctksFkzL8jsckZh18znTmF+Yyfef28imvXV+h+M7PVAqyj37XiV3vbKdq+cVcMOi\nKR9b39uDc0Rk4IIB4+4vnM6Su5fztUdL+MMtZ5GTNnpneVAPJIr9eeM+/sfT6zlzehb/pnEPkWGR\nm5bEAzcUU3O0la//umRU36WuBBKlXtt6kG89sZY5kzK4/4vFJMXrbnOR4XLKxHTu/Pwc1lYc5quP\nltDUOjqTiBJIFHq6pIKvPVrCiePTePhL80lJ1JlIkeF2yal5/OSq2SzfcYibHl09KpOI/vJEkc5O\nx89fLeXOl7dx1vRs7v2buaQlxfsdlkjM6Wvs8PoFkz9c/ty8Aszgn55ez7UPrOD+L85j/Ci6gVc9\nkChR1dDClx5ZzZ0vb+Ozp0/kV186Q8lDZAT47NwC7v3CPLYfaOCyn7/Nml21foc0bJRARjjnHC+8\nv49LfvYWK8uq+fGVp/DTz88mIU6HTmSkWHzKBH7/jTNJjg/y+V++y3++9MGoGFzXX6ERbPPeeq5/\nYCXfePw9ctISWXbLWXxhwRRdbSUyAs2YkMYfbzmLK0+fyD2v7eDSu97ilS0HYvqudY2BjDDOOVbu\nrOGXb+zgta1VZIyJ59+uOIXr508mGFDiEBnJ0sfE85OrZ7NkTj7ff24jNz1awuyCdG65oIjzZ+QQ\nF4yt/9nDSiBmthj4GRAEHnTO/Ue39YnAY8A8oBq4xjlX7q27HbgJ6ABudc691FebZjYVWApkAu8B\nX3TOtfb1HtHOOce2A0d4ceM+nlu7h/Lqo2SlJPBPnzyRGxYVkj6m97EO3SgoMvKcXZTDy98+17vR\nt5SvPVbC+LGJXDWvgMUn53HKxLExcSah3wRiZkHgHuCTQCWw2syWOee6To5/E1DrnJtuZtcCdwDX\nmNks4FrgZCAfeNnMTvS26a3NO4A7nXNLzew+r+17e3uP4/0B+KGxpZ3tB4+wofIw63YfZvmOQxyo\nb8EMFk3L4pvnT+fy2fm6t0MkisUHA1xzxmQ+O7eAV7Yc5MnVu7n39R3c89oOxo9N5MwTsjl9yjhm\nF6QzNTslKi+KCacHMh8odc6VAZjZUmAJ0DWBLAH+l7f8DHC3hdLrEmCpc64F2GlmpV579NSmmW0B\nLgCu9+o86rV7b2/v4YbhBKNzjk4XelhTp3M4B53O0eEcbe2dNLV10NzWQVNraLmprYOm1g4amts4\n2NBCVZfX7pqj7K9v/rDt7NQEFkzL4pyibM49MZcJ6aPnEkCR0SA+GGDxKRNYfMoEqo+08NrWKl79\n4ABvbj/Es2v/e1LG7NQEpmSlMCVrDPnpyWSMiSc9OZ6MMQlkjIknOT5IQlyAhGAg9PXYKxggLmAE\nzDBjWHs24SSQiUBFl+8rgQW91XHOtZtZHZDlla/otu1Eb7mnNrOAw8659h7q9/Yeh8LYhwF58f19\n3Lp0rZcwjr+9tMQ4csYmkpOayCemZ3FCTion5KRyWkE6eelJMdGVFZH+ZaWGTmNdNa8A5xwVNU1s\n2lvHrpqjlB9qpLy6kXdKqznY0Bzx3x4zCJjx9XOm8Z3FMwd3B7oJJ4H09Net+671Vqe38p5Gkvqq\nH24cmNnNwM3et0fMbGsP22UzBInHJ7GyL7GyH6B9GakGZV++MAiBDIJ+9+W7/we+G3n7H5+ZtQfh\nJJBKYFKX7wuAvb3UqTSzOCAdqOln257KDwEZZhbn9UK61u/tPT7COXc/cH9fO2RmJc654r7qRItY\n2ZdY2Q/QvoxU2pfBF841ZauBIjObamYJhAbFl3Wrswy40Vu+CnjVG5tYBlxrZone1VVFwKre2vS2\nec1rA6/NP/TzHiIi4oN+eyDeeMMtwEuELrn9lXNuk5n9EChxzi0DHgJ+7Q2S1xBKCHj1niI04N4O\nfNM51wHQU5veW34XWGpmPwLWem3T23uIiIg/bDT+E29mN3unuqJerOxLrOwHaF9GKu3LEMQxGhOI\niIgcv9i6r15ERIZNzCUQM/tPM/vAzDaY2e/NLKPLutvNrNTMtprZxV3KF3tlpWZ2W5fyqWa20sy2\nm9mT3oD/iNBbzCOJmU0ys9fMbIuZbTKzv/fKM83sr97P9a9mNs4rNzO7y9unDWY2t0tbN3r1t5vZ\njb295xDvT9DM1prZ8973PX4+vItGnvT2Y6WZFXZpo8fP4DDvR4aZPeP9nmwxs0VRfEz+0ftsbTSz\nJ8wsKVqOi5n9yswOmtnGLmWDdhzMbJ6Zve9tc5fZENxw5pyLqRfwKSDOW74DuMNbngWsBxKBqcAO\nQgP4QW95GpDg1ZnlbfMUcK23fB/wd37vnxdLrzGPpBeQB8z1ltOAbd5x+L/AbV75bV2O0aXAi4Tu\n+VkIrPTKM4Ey7+s4b3mcD/vzbeC3wPN9fT6AbwD3ecvXAk/29Rn0YT8eBb7qLScAGdF4TAjdXLwT\nSO5yPL4ULccFOAeYC2zsUjZox4HQFa+LvG1eBC4Z9H0Y7g/vMH/ArgQe95ZvB27vsu4l74e7CHip\nS/nt3ssI3ZdyLBl9pJ7P+9VjzH7HFUbcfyA0/9lWIM8rywO2esu/BK7rUn+rt/464Jddyj9Sb5hi\nLwBeITTVzvN9fT6Ofba85TivnvX2GRzm/Rjr/dG1buXReEyOzU6R6f2cnwcujqbjAhTy0QQyKMfB\nW/dBl/KP1BusV8ydwurmK4QyL/Q8JcvEPsr7mlbFb73FPGJ5pwtOB1YC451z+wC8r7letYEeo+H0\nX8B3gE7v+7Cn3QG6Tu3j935MA6qAh73TcQ+aWQpReEycc3uAnwC7gX2Efs5riM7jcsxgHYeJ3nL3\n8kEVlQnEzF72znl2fy3pUud7hO49efxYUQ9N9TV9SlhTp/hkJMf2MWaWCvwO+AfnXH1fVXso8/1Y\nmNllwEHn3JquxT1U7W/anZFw3OIInTa51zl3OtBI6FRJb0bsvnjjA0sInXbKB1KAS/qIa8TuSxhG\n5N+vqHyglHPuor7WewNJlwEXOq//xuBOq+K3cKaXGRHMLJ5Q8njcOfesV3zAzPKcc/vMLA846JX3\ntl+VwHndyl8fyri7ORP4jJldCiQROg30Xwx82p2RcNwqgUrn3Erv+2cIJZBoOyYAFwE7nXNVAGb2\nLPAJovO4HDNYx6HSW+5ef1BFZQ+kLxZ6UNV3gc845452WTWY06r4LZzpZXznXfXxELDFOff/uqzq\nOi1N9+lqbvCuOFkI1Hnd+JeAT5nZOO+/zk95ZcPCOXe7c67AOVdI6Gf9qnPuCwx82p3ePoPDxjm3\nH6gwsxle0YWEZoqIqmPi2Q0sNLMx3mft2L5E3XHpYlCOg7euwcwWej+bGxiKv1/DMVA0nC+glNA5\nwXXe674u675H6AqLrXS5IoHQFQ7bvHXf61I+jdAHqRR4Gkj0e//6i3kkvYCzCHWbN3Q5HpcSOu/8\nCrDd+5rp1TdCDxrbAbwPFHdp6yvecSgFvuzjPp3Hf1+F1ePng1Av5WmvfBUwrb/P4DDvwxygxDsu\nzxG6eicqjwnwv4EPgI3ArwldSRUVxwV4gtDYTRuhHsNNg3kcgGLv57IDuJtuF04Mxkt3oouISERi\n7hSWiIgMDyUQERGJiBKIiIhERAlEREQiogQiIiIRUQIREZGIKIGIjCBm9rqZfdXvOETCoQQiIiIR\nUQIRGSIWeqDWs2ZWZWbVZna3mX3JzN42s5+YWa2Z7TSzS7z6PwbOBu42syNmdre/eyDSNyUQkSFg\nZkFCz6fYReiZDxOBpd7qBYSmzMgm9AChh8zMnHPfA94CbnHOpTrnbhn2wEUGQAlEZGjMJzTF+D87\n5xqdc83Oube9dbuccw845zoIPR0wDxjvV6AikVICERkakwglivYe1u0/tuD+e8bo1GGJSmQQKYGI\nDI0KYLL33ImB0OymEjWUQESGxipCU3X/h5mlmFmSmZ0ZxnYHCE1HLjLiKYGIDAFvfONyYDqhBx9V\nAteEsenPgKu8K7TuGsIQRY6bngciIiIRUQ9EREQiogQiIiIRUQIREZGIKIGIiEhElEBERCQiSiAi\nIhIRJRAREYmIEoiIiERECURERCLy/wFMdYgcL9SQqAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5012d47690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "sns.distplot(data.cnt.values, bins=30, kde=True)\n",
    "plt.xlabel('cnt', fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##计算不同天气的平均租车数量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "晴天,多云租车人数4876\n",
      "雾天,阴天租车人数9141\n",
      "小雪,小雨租车人数107521\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f5009244150>"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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2e4ArgMOA28pDOmhkJr9ZsYqVy7vYsHYTr/yDY5j+mmm8ZNJhrZ6aNCjRuzBp9Ghvb8+O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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50130702d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "weathersit = data.weathersit.values\n",
    "\n",
    "weathersit1 = np.sum(weathersit==1)\n",
    "\n",
    "wdata1 = data[data.weathersit == 1]\n",
    "\n",
    "wcnt1 = wdata1.cnt.values\n",
    "\n",
    "twcnt1 = np.sum(wcnt1)\n",
    "\n",
    "wt1 = twcnt1/weathersit1\n",
    "\n",
    "print \"晴天,多云租车人数%d\"%wt1\n",
    "\n",
    "weathersit2 = np.sum(weathersit==2)\n",
    "\n",
    "wdata2 = data[data.weathersit == 2]\n",
    "\n",
    "wcnt2 = wdata1.cnt.values\n",
    "\n",
    "twcnt2 = np.sum(wcnt2)\n",
    "\n",
    "wt2 = twcnt2/weathersit2\n",
    "\n",
    "print \"雾天,阴天租车人数%d\"%wt2\n",
    "\n",
    "weathersit = data.weathersit.values\n",
    "\n",
    "weathersit3 = np.sum(weathersit==3)\n",
    "\n",
    "wdata3 = data[data.weathersit == 3]\n",
    "\n",
    "wcnt3 = wdata1.cnt.values\n",
    "\n",
    "twcnt3 = np.sum(wcnt3)\n",
    "\n",
    "wt3 = twcnt1/weathersit3\n",
    "\n",
    "print \"小雪,小雨租车人数%d\"%wt3\n",
    "\n",
    "wy = np.array([wt1,wt2,wt3])\n",
    "\n",
    "wx = np.array([1,2,3])\n",
    "\n",
    "plt.scatter(wx,wy,c=wy,marker=(3,1),alpha=1,lw=12,facecolors=\"none\",s=500)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##计算节假日和非节假日的平均租车数量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "非节假日租车人数3735\n",
      "节假日租车人数4527\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "holiday = data.holiday.values\n",
    "\n",
    "holiday1 = np.sum(holiday==1)\n",
    "\n",
    "hdata1 = data[data.holiday == 1]\n",
    "\n",
    "hcnt1 = hdata1.cnt.values\n",
    "\n",
    "thcnt1 = np.sum(hcnt1)\n",
    "\n",
    "ht1 = thcnt1/holiday1\n",
    "\n",
    "print \"非节假日租车人数%d\"%ht1\n",
    "\n",
    "holiday = data.holiday.values\n",
    "\n",
    "holiday0 = np.sum(holiday==0)\n",
    "\n",
    "hdata0 = data[data.holiday == 0]\n",
    "\n",
    "hcnt0 = hdata0.cnt.values\n",
    "\n",
    "thcnt0 = np.sum(hcnt0)\n",
    "\n",
    "ht0 = thcnt0/holiday0\n",
    "\n",
    "print \"节假日租车人数%d\"%ht0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5010056510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##一年中各种天气出现情况\n",
    "\n",
    "sns.countplot(data.weathersit);\n",
    "\n",
    "plt.xlabel('weathersit count');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f50129e6410>"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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A+4FvAl8Hzp2GXN3+O4D3LEeeIV6v9cCXu3+PNwDPm5Jc5wC3dcd8EPiJxR7TM1klqVEt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\nWfCS1Kj/B9Dvjy+VIA0EAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5009308e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##气温分布情况\n",
    "\n",
    "sns.distplot(data.temp.values, bins=30, kde=False)\n",
    "\n",
    "plt.xlabel('temp', fontsize=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f50132d24d0>"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50132e3cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##风数分布情况\n",
    "\n",
    "sns.distplot(data.windspeed.values, bins=10, kde=False)\n",
    "\n",
    "plt.xlabel('windspeed', fontsize=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f5013285250>"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50123ec8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##atemp分布情况\n",
    "\n",
    "sns.distplot(data.atemp.values, bins=20, kde=False)\n",
    "\n",
    "plt.xlabel('atemp', fontsize=12)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f5013961ad0>"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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kJgy6JDVh0CWpCYMuSU0YdElqwqBLUhMGXZKaMOiS1MT/A8P7h3ylzx8aAAAAAElFTkSu\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5012c05290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##atemp分布情况\n",
    "\n",
    "sns.distplot(data.hum.values, bins=20, kde=False)\n",
    "\n",
    "plt.xlabel('hum', fontsize=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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L4GJoIMOGDjBZbmNjw1+r/+BiaCCHA30pUcLdsOyHYQO5GBrI+XMBeLVobJi/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BAAAg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\n8J7bi8vszm93vpmdcvbMmUlgYEj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zdACEYwmKDBqB4uAMQMK341AjQi2Wza15dWpN7Y9Q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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5012dd7f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_corr = data.corr().abs()\n",
    "plt.subplots(figsize=(13, 9))\n",
    "sns.heatmap(data_corr,annot=True)\n",
    "\n",
    "# Mask unimportant features\n",
    "sns.heatmap(data_corr, mask=data_corr < 1, cbar=False)\n",
    "\n",
    "plt.savefig('house_coor.png' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xLW1HMWXNy7j/+QO4Y8YVhoIAO3LdNkU5jzW7D2P9wlqsnDMZq26tRkvbUVSv\neRlLWg9kdQGOxpI43RPNiYpSvF9i6xSz2ojKa7hRVSqNVDSWQHeEG3z+rfvRyyUwujwwItSZuYTC\ngwThAqchMrP9n39ZPAvHz/UZhqVaGmowd9NbrkNuuQw7aefRMH08/ul7NXhw+0c529vK5Z7WoMBD\nQKnfI1bH2NFheg2nz9tp2xbpGZudZ4RDycUEkW2c1sszk0xHuaRpWEqqVu62K3IuE3RLfSxaGmpQ\nNaZMrgpRXuLLKHRnZ2Sl1AOfl8W25vqsqQeVhqWloQYtbUcxujwgz+90TxQhTeV8p89bm2huFt5U\nVqTPR/fr4QCFBwnCBU7DcWZ7TV/1x9CX6umk/beu831564pshLTIS2HAlrajWHVrNc5fHEg7dOd0\nT1BKPSgrSe2xlWTeTVhpWKQK9Bd6OXx3y9tY9Mt9CAW8KPGq77vT5619STELPZ7uiea1+/VwgMKD\nBOESJ+E4szJAG17txMwJl+D2aePURVubxKKt/XG+YFRlZiHOX95dj2gsIec6uZGDD5Vs3ghtqE/q\nmjx5bJnlc3SSL2YURv3JbdW68GYo4EWJj9SDJlB4kCBygZNwnDZJ+Pi5Pmx4tRNtB8+g7eAZdJz+\n02DoS7GAlQUKJ/hhFuIs9XtQ6nPeDsTJOe1Ci06L3EoYvVhE4+pQX9vBM7jQy1lW8DfK1TIaqzbR\n/EIvh4CHxePfr8X4S0rl0KOUuE4hwfTJ6V8IwzCXMAzzW4Zh/othmE8YhrmeYZgKhmFeYxjmeOr/\nL019l2EYZgvDMF0MwxxiGGam4jx3p75/nGGYu3M5ZoLIFpJxi8aSaGk7iraDZ+R/O3eRAxg47kCc\nD6zk9G47KMvn5EzOyZmHFqV2IpLsXFIrJpO84feNQ5AcWABPLZrpWGnpRDkoKQbBAKU+D351j1j+\nq6WhBv/8u09ww+Nv4JpH9mDOxt+jhEKBWSHXr3WbAbwiCMLXAUwH8AmAvwfw74IgTAbw76mfAWAe\ngMmp/y0B8CQAMAxTAeB/AZgF4DoA/0sydARRDORalu4GN7UDczFuloVxu3uLlSgaT2L5zg6V8Vi+\ns8NULm5sbDpwvpdDLMnLhmXb3fWWIU07r1BnHFv3I8IlMRDXv6RQkd3skTMflWGYUQBuBHAPAAiC\nEAMQYxjmewBuSn3tOQBvAlgN4HsAWgVxk+0/Ul7auNR3XxMEoSd13tcA3AZgR67GThDZxG09wVzh\ntnagctwhZkX8AAAgAElEQVTZqgpR4htsdy8pEje0d2LjnWHTY0IBr6HxCJmE2MyMzZUVQSz65T5s\nu7te9hCtsFMOahWDo8sDiHAJVJb58fRddXj23ZPY8npXVmpSEoPkMrA6CcAFAM8wDDMdwAEAywGM\nFQThLAAIgnCWYZgxqe9fDuC04vjPU5+ZfU4QRUM++kZpSaf/l1QVIlt1+KKxpGG7eyvpdySlttQa\njwiXQHmJz/AaRt/vOt/nSppvVxBZaRzN6hgunV1VUOKa4UAuw4NeADMBPCkIwgwAEQyGAo0weqKC\nxefqgxlmCcMw+xmG2X/hwoV0xksQOSGX7TxchfvSFEGY7u2kEe5KJ+QY9HmwuTGsOmZzo3GPM7Nr\nPLagFk+80eUqTKf0NI3Cico9v6U3V2H1i4fUIcwdHeiP8wW7Z1ms5PKV73MAnwuCsC/1828hGq1z\nDMOMS3lZ4wCcV3z/SsXxVwA4k/r8Js3nb2ovJgjCVgBbAVHynr1pEET62IXkMqlm4Tbc5zRRVjq3\nNC5TYxfwgOcFVwtyOqFSj4dFZciPrc11jtSD8jVS6sxT3VFsfK0TF3o512E6Kw9Z6YlZ1TEUyzqR\nxD1b5MzTEgThvwGcZhimOvXRdwD8J4A2AJIC8G4A/5b67zYAzSkV4Z8D+CoVRmwHcCvDMJemBBi3\npj4jiILHSoHmpviu23Mb4dTL0Y7rVLdxHcBT3dG0auelozz0eFiUl/jAMmK1DDODpVTzgQEEXsBl\n5QFsvDNsK7xIZx6SAe43UVqe6o46erbDobnmUJFr9eD/BPAvDMMcAhAG8DMA/xvALQzDHAdwS+pn\nANgD4ASALgDbAPw1AKQEGP8M4MPU//5JEmUQRKFjFZLLtMW91bmNFkG7cJeEdlwbXzumU/w9tqAW\nm/YeMw0t5mMRNnoJ6InGRQ8nR6kFkgEO+vUvBOsX1mLja8ccFdrN5OVlpJHTHWFBEDoA1Bv803cM\nvisAWGpynl8D+HV2R0cQuccqJJfuHpPduQfiSUS4pGnY0E4QohUYLL25Cv9jVAm2Ntch6PeKir9X\nxXCbWWgxHw0U0xGaZAtd2JNLYs3uw2g7eEa+h1VjytAfS+pCqvkcdzFSOOn3BDEMsQrJZdoLy+zc\nPI+MPDhpXJIirqXtKL7+D69gSesBnP2qH0++2WW5P2Ql3Mil12X1EjAU3p4y7AlGTCBX3sPqNWIu\nl9aLyvTlZaRBtQcJIseYiS2y4ZEYnRsMMuowLI0rwiWMuwc31wMMTIUFZu08OtfOw6Jf7suZ12VW\n11Cq6D4U3p6E7T1UeFH5rMdYYFDnYoIoBMyEB073mNyeO1MPThrXhEqT7sEBj+X+kNn1u8732Xp9\nTvbCzL5jJXUf6qaLtvdQ4UUVUsWUYmBEmXGCKDScJh27kcbbJcU6HZfUQmV0eUDekzndE8VAPCkX\nfnV6fanCPWAe+nLieYrf4TQV5gcbN5oVKba6bq5Q3kOrNINCqZhSLFB4kCAKGKk1RoRz1wrEaUsN\ns2MlA9k3kEAsmcT//H8tuvsahSgB+TMxT+qYbDzMQl9OwmR9AwksbjX4TnM9ykq8rs41FORLlFKk\nUHiQIIoZacE7f1H0LNwKKyJcEotbB4u5OpFRa+XX9z9/AANxHqPLA6ris9K1zeTaQMpzFMTagRd6\nOdPQlxTuC/o9aGmoQcP08fK/6UJpAfNEZyWFEnLLRgiYUEPhQYLIE3YhP0mFt/3Hs1yry9KVURsd\n99CuQ2hpqDEMs9ldxy70ZdYsExD7XWlDaVEuiWWzqzB36ji54G77kbOIckmVp1VIIbdCqDs5nCBP\niyDygJOEUkkKbda63UpY4aSthqGYweS4qjFlhtd2Itc2E6LwvIBILIGKkB8tDTW4fdo4vH+iG6tf\nPISlN1cZekdeFmi8boIsIW9pO4rG6ybAa7CSpdvziyhsyGgRRU8xlsBxUg1DUuE98UYXHltQ6yrU\nZaUgtDKYZsed7okaXjtdpaI0hiWtB2Tjs+rWajRMH48PP+3B5LFlhqG0BA/D3loJ436QBIrz78MK\nEmIQRU2xbnSb5TIpc6mSSR7d0RiW7+jA2FEBrJgzBRMqg45EFVb3JRpPmooUjNqQbG4Ko8zvRYnD\n8J6T+2+XU7Xt7nqUellE40lVkVyGZTLKQRtpFNnfh6MBUYCVKGqKtQSOXcV1nhfQE41j575TaGmo\nwTWjQ+iXvDCbP21pr6wi5JMroyuNjVVIj2UYVAR9ePou8biu833Yue8UmmZdhRKfRx6bJJyIxpOo\nCPpc7x1ZhSG3NM1AiYdFdySG5TsHVYubG8MoC3gdV6onivfvwwoKDxJFTTGUwDEKz9ip26TFZuPe\n43jijS6c+dMAlrQesC2oqgz9Va8RSy9198VUhsQupNef4HH/8wdwzSN7MHfTW9i497hlZfp0itKa\njyGBypAf/YmkYRgwKQhpqwKHW5jMCcXw9+EWMlpEUZNp9YdcYyUJt5JCKxcbowaDZpJ3J3tlxgYz\nDJYRx+u0Mv3t08ahpaEGFSE/IrHMq1dsaZqBkF80eqGA13AMoYA3LQn5SK2kXuh/H+lARosoagol\nH8cMKyNipW5TLjZWDQa1OFXzSU0Sjz06D+vmT8Ojv/sEP3pWXMgH4sYLXUSRS9XyV99QFYJd0npA\nZwSsDIUuf6m5HqGAWDexj0sgkqokYTQGO1WgkaHMtA1MsVLofx/pQEaLKGoKPXkz3fCMcrExk7z3\nDei9G6dv1iwrViL/4bZ9uGnDm9jdcUZeyHkeuoVuc2MYz7xzElN+Kir9/q8ZV9h6f9GYtaGQ85cE\noD+exI+eHTRuDIDNjWHdGOwWWzNDWepjh12YzAmF/veRDmS0iKKnkPNx3IRnlB6CUuBQNSaEzU3q\nBfyxBbV49t2TOk/BzZu1qUENeFQL3dbmOuz84BQ27j0uG5+yEuPwnTIPzLR6hcZQGHlBi1sPYFSJ\nF1ub6+QxVIb8th2LTQ1lHsNkme6lZXp8If99pAMZLYLIIem2uFcKHDwsi8pUAm7n2nloaajBhlc7\nseX1Lp0BcPNmbbqQc0lVpY5QwIstr3epvmeX8ByNJ3GqO+rIUJgZT7/Pg/ISH1iGQXmJz9JgSfeu\n1ORcoYA3L2GyTPfSRupenBVktAjCBW7fetNtca8NpfXHebS0HZUVfcoSR9pxReNJR2o+M0FGkudV\ni2TfgH5/qf3IWZ33pzQCQb8Hm/YeM0iK1of4MvWClPfOypjmI0yW6V7aSN2Ls6I4hfoEkQfSTdS0\nqj2nrD9oFUqzajeSybi09flYBvjRs/tVeT3PvnsSm5vCWK6oMt806ypdfpaUDBz0exDhEjh3kcOG\nVzvR0lAjtzUJGRjRTFupKO+dVD1k9YuHdOdyUgPQTQsYt2OTcLOXNhwl65lCRosYtlgtQOksTtlO\n1FQam5aGGsukWbMCsAAQiSWMx6Vp12E276Av9d9+sYXJ2FEB1TFbXu/C0tlVhgnEZamQXamXRSQV\nSjx+rg8nLvRic2MYy3d24Ltb3paNR4lXv9hmWtxWmagtFfVdN3+aWD3ExblyUT3CLok818cPRyg8\nSAxLrPYC0t0nyPZbr9IIplNfUBDEeQT9JqKIgMeBBJ1D70B88LPW/Vg1t1rVHuTaqyvQH+dNN/N5\nXkB3NIb7nx+sI1gz/hIc+KxHFlLYheMyEQtow5wXejmEUqpEN+fKRSguU8n5cJSsZwrVHiSGJVZN\nAAGk1SAw240FtfUHG6aPx9KbqzB5bJlljT9lHcJzXw2AZRiseKFDN65186fhsvLAYANFk/Gvmz8N\nN214U/fZnI2/d+RtWNURnDy2DBCQ1ZCbEdkI69nVg0z3Gk6PM/tetkOWBQw1gSRGLlZeUTZyp7Lx\n1qsVILQdPIOWtqOqkKD83ZQXMLo8gJW3VOPhlw5jyk9fxq79pxHwsVi/UO2lbVg4HZv2HlM3UDSZ\n95UVQd1nEyqDjgULVnUEB+LJIVG/ZUPWnW5l/GyMzS4RezhJ1jOFjBYxLLFagNJVq2U7UdOpEUwm\nedkwaEs6zZ06Dg9u/wiPv9IpS+LXzZ8GQMC5i5xqTlZtR4zuhdNF0uy8ES4BnodlyK2Q6gFaPY9c\nq/hIJeickbmTRwx77BRp6arVstmF1kpcIVVRj8WTuDiQkA2DtqST9HOCF2QRgpdl0Ll2nm5ORvfk\n5z+YDl9qgU5HuWd23s1NYYT8YisRM6/WqfBhqMJjVoIQt9652zGTStA5ZLSIgiGbi5OdIq1QW7Fr\nF/L9a+Zg+c4OjC4P4LEFtTjdE1WpyaS8JL26LKFb/LX35FR3FP/75f8CAFmWHo0l5KK1buZgdj/7\nUjUEjdRvAGzVmEPdD8rspcSNii+dMQ+1SrCY98koPEgUBLnI/LfaCyjUfQJtmGhUqQ8fftqDtoNn\nsOHVTpSXeFRJve1Hzupq9CmrpWtRLspzNv4ebQfPoO3gGczd9Baq17xsmEflFpYRF2FeEMAywBaT\nJGQn3kWhhM3c7GemM+ahVAkWe5UN8rSIgsA0B6q5HmBQlG+ERti94WoX8ov9cdUbeITjsfvjz2XP\nqG8ggRNf9OLpu+pQVuI1vUfa67IMsvZmr1U2rppbjYd2DSb3PrVoJrY11yMY0OSXWXhh0hhyETZL\nx8uQvMlf3VMPnoc4F27QCCnPmc6YM81Vc0OxN4YkT4soCKyKtxbrG6EWJ2+4SlFDw/TxiCd52VOR\nRBgb9x7H3E1v4ZpH9uCB7QdQNabctlVHdySGX799AsfP9aHU50EiKWBbc11W3uyVi+CDN1XhoV3q\n6u8PbP8IYCCPDwC6IzE8885Jy9w0nhcMS0hlUug2Uy8jwiWxuHUwp607EkMyyavO6bTmopah8v6L\nff+s8M0qMSIwi+mf6o4W7RuhFidvuFKYaMe+z3DHjCuwbEcHxo4KyBUezIrBsoz5AheNJ+XzKcsb\nbW4K41f31CPgZeXCuG7f8HleAARg+49noet8n6PeX6pagRci2LCwFl8r9eu8l2g8iWffPakry7TZ\noH6h2di0HlUmXobZsVub61Sfb3ztGNYvrFV5m4WUEFzsVTYKf4TEiMBY7RfGo7/7RPW9Ynoj1OKm\nQeO935qIJa0H5IWFF4B/+p51qSer686dOk6WygPigrt8Rwe2NteBYRh098XwD7uP4NxFzrHQwUhw\n8NSiOtchvyQPLG7drxMtBP0ebHm9C10XInI4tOt8X9pj29I0A5VlfttnYBY+NHt+2i7LbQfPgGWg\nC4kWSlg701qP+YbCg0RBYJQDFQp4ce4ip/peMbcKd9OgUbkQNkwfj1W3VqP1vU914bTNTWGUeq3/\njKOxpIUH5MWUn76Mh186jJW3VGN0ecCx0MFIcPDceycNhSHKBVF5H7R5Z0rRgvQ9SShyzSN70NJ2\nFP1xPq2xLdvxsWlHZGW1fGWo79dvn5DzyCJcAstmV+mONTrnuYucKiTqtHKGm5y1dHPcir0xJBkt\nomDQxvRLvMOr7porBZrBwr5x73G5anrn2nl4ctFM7Nx3Cj3RuOWCFfR5TBfrrvN98qK++sVDWHpz\nlSqPympRNPI8trzehcoyP7ZJNQeb6xEKqOenvA9W4USz+1XqZVXjSiZ53TitvFqrZ6A0drdPG4c7\nZlyB+58/gCk/fRlLWg+g8boJWDlnsu7YdH5PVfd3IKGuAWmz15bp3lyhqmedQLUHiYLGKFQD5L6W\nXa5wU4dOCm9t//EsVK/R18TrXDsP1zyyx1H9w2SSR3c0pmov8tiCWmx4tVOXlLzol/uwrbke/akF\n3CzXyKzm4K/uqUeEsz5Wug8QxNCg9hxbm+sQ8ovzUd6vUi+LnmhcncjcGMbOD05hy+td8rVKfR7D\n8267u17e2zKs/q+oP9i+4ka0tB01Hptm/8+tItEofLl+YS0ef2XweVg912zXwSwQqPYgUfxo3wgB\nFHWOidM3XGUIp98krNh1vg+As30+j4fFZaGAHBLa2lyH3R9/Li+Q0jlP90SxpWkGWNa6/BJg7jna\nlW5S3gcjz+exBbV45p2T6I7EAEB1v/oTvO7cy3d2YO7UcaprsSxMvR/lM5AMmOSlRbnBe23mBYYM\nnp9bz8UofPnQLtHTVV7L7LkWuwIwE4rWJBMjk0LNMcllhYFgwIOn76rDs++elL0JyUsCBvdkrDwI\nQJ1YHPJ70TTrKrx/okclfAmlwrJg4Fg0oitD5eBY7Tm2Ntch6Pei63yf7P29f6JH91ytivMqfy7x\neVDi9chji6TKYsldnVPekV5IMhNbmsJYtqPDotpI5io7J/OwulaxKwAzYXjPjhh2FOIbZi5KDRmd\nc3NTGEtnVyHCiVLwPYfP4vpJlXhq0UywALojHJYpwn9WY7BLZlWWX5JaplSNKUOEU5d5Mip7ZFW6\nyWxBDQW8urYgRs/VbLGWvE7ttYI+D7r7jJ+N0QvQA9s/wq/uqce2u+tR6mN1HZuztadqNo/TPVF4\nWcb2WsWuAMwE2tMiiopCjOVnvc8WLyASS8iexxNvdKHt4BnxnM1iPzApp8nLAr1cAhEuiYdfOpzV\nMXRHYob5XXYG2cyIVwR96E/whvUJv+jlHI3f0Jgb7GlJ47PadyvxeUz7Z0FATntZGd+jlKfrc74v\nVqx7uyY4GjwZLaKoGOoCqo7GZNM80NW5DOYnhQL3HD6LzrW34XRPP66sCOJ0TxSXBH1ofe9TLJ09\n2VCskc4YlGOJxBKqfDFAbUycNi40ElDIhizOo9TvQd9AAs+9d1JhfMKoDAVsS1KVellwSV5VXino\nT43D4NncER6Pn373z0wN/br50xAKeA2FI9k0EMPQ6GSKo8lTeJAoKoayRptTTPcXuKRYN9HF+IxC\nVqtfPCQm144OobsvhodfOqxSnC2ouyIn+y/afDEJp61FlGHDPi6hm9eOfZ+hcdYEVfhtU2MYf31z\nFT7/st+0eK9RZXwztWI0rn82K+ZMwbIdg5XzlV6k9IJwoZdTGeZcvChls82NluFsEEk9SBQdhZZj\nYqSiW7+wFmt2H06pGznH6karDfp7vjkRy3d26BRnXyv144k3uizr+LlFyiECgL0rv42G6ePlf5Ob\nabqoZm40r7lTx2H5DvV8VuzskA1WidfZ2KMxk3GkFmvts5HKYUmV86W8t23N9bIIRLmflo1K80PZ\n7LLYq7jbQZ4WQWSIUZ8qZb7Nsh0d2NZcj7IS+z83c1VYAmUlJl5PwIMLvRw2vtYp1yhUhsjcYpZD\nxDJipYenFs0EBDEU19JQI++5yePxDxa8ld72pWoSG/cel69jJimfUBkEUuur1AzTqnp9MCAaRKVg\npOt8H0r9LMAApT6PvIc1EE+qqstLrVmun1SJloYaeR4qMUeG4p+hDmkXqsI2WxT/DAiiAJC8P14Q\nMGfj7/UquICzBa7Uy2JzYxjLd3aohAalPg/++GW/SRgyoQqXQoAjA2mG0aL30K5D2NZcD5YBIrEE\nlm3/SBVSA8Sae0r5vZFgAoC8Z2XVmsToeKOFPhpP4oteDstmV+kLAjeG8bM9n8j1FP0si0RSQFnA\ni6cW1cn7Z8tmV+Geb05EWcCL9hU3ov3IWTTNumowkT1DeflQG5FCVNhmEwoPEkQWUSanSsj7Ww7o\nT/DY+cEpOWTV0lCDnR+cQn88iX/96HNsWDhdV3sw6Pe6CpemU55JMrxf9cexTBPSk8o/KUOSRiG1\n5Ts7cO+3Jg7WljQsqRQGywBgxH5bo8sDpiE5qVzTpr3HcPdfTNTVMFy+swMP3lSlOvb+5w9gypqX\n8cD2A7jzugn4r3+6DY2zJsift7QdReOsCagI+uT7mGmDxqE2Ik5rXBYrpB4kiCwSjSXQE4mp2lKs\nX1iLipAfQb/9W7WVErG7T5Sgz506TpEz5YHH4/zd00moSikTV4bcegfiKC/xonrNK4bjU6kHU/O4\nfdo4VciuakwIHpZVjUcZQuR5AQ9ovDhpn0l5HUmNyAsC+mNJTKgM4vi5PlWoUlnqSvnfEtdPqsST\ni2biwe0fOZLapytsGOo0jUJU2DqE1IMEkSvMFrESrwflAS/WzZ8my9LLXYoKzEJRlSE/7rthknzN\ndEQo6fT00obctHtTkiepDElGY0njkF1TWCyGrMhFkhKAI1xCJUFXKiel0OPZP/UjnhRwWVkAO/Z9\nhgV1V6rUlNpQpZR0rE1ABkRvZ1Spz9QLSib5wbwyqZKGopyYU5T3U/nCYVed3wgnxrMQFbbZhMKD\nBOESK3UWyzIoL/HhsvIAGAa4rDyA8hKf4wXDKhSVDdWkUahq7KgAIEAOFwKQe3oZhdzu+eZEnVKS\n1awkQZ8H93zT4PgdHTh/kVPdt4GEaEivrDBuclk1pky8D41hAAwefukwSlM9wlbtOmgaqly/sBZP\nvtklh1Hbj5xVndusrci1V1fg3FcDWVPgsSyDiqAPjbMmoKXtKKrXvIz7nz9gWJ3fKnTrRhVYaArb\nbELhQYJwSTbDPUNdxT4aS+D8RQ5XVgTRdb4P7//hC8z5xlhdl92KoA8My5iGKv/4ZT/GX1KKrvN9\nePLNLmy8M6xLYjYLdSrDdFKVjzW7D6OloQblJT7DKiB//FM/gn4PfvJb0Qi2r7gRVWPKTBOqo1wS\nLAvZozOsDt8URkWpHz3RmE74wjCQ9+4kMgnpOfmdsQvrFWI1mCxD4UGCyAVKb0W559MfS8relhOs\nFik3Sadu2p1IITi5QOxddXjg+QO6cOHTd9WZqvv+FI3jhsffkD+7flIlolwCYBhda3u7OoEfftqD\nUj+LVXOr8aBmL6tqdAhNs64CywItbUex/cez5Pv+xBtd+OfvTTVX9SlCldI9NAqZReNJWfgi7bsd\n+KwHc6eOy1g8oXwuVmKMPi6hE68on4VklNIRdAzHJGMKDxKES6R9J6mjsBTyWdzqLoSUraRVpyEj\n8Xpq5V+ZScWLUMCLdS//FzbeOV0fCmSgaoS4uTGMJC/oxlDqZQ2Trp94o0u+1rVXV4CL80gkBWz/\n8Sz8btkNGF0ewOoXD+Heb01EZcgvNwM93ROVQ3ltB8/g41M92Nxk3CXZKMxmFDIL+j3Y8nqX3Bn5\niTe6UDP+EpzqjhqGDZ0q8LTPxex8x8/1yffLyihJLxxuxjRck4zJaBGES6R9p5W3TDFtFe/oPFmQ\nQjsxfNICHvSLycDK6hZS+SclkjfUdvAMeF7AuvnTZPn946904sHtH6H5L65G59p5eGpRHQQAD6QU\neMox9Cd4dVv35nqUB7y40MvJRuapRTMRiYneX3VKcr7q1mqMHRWQyzhJwoIxowLYkjJSd4THo2ps\nOXbuG0wPePquOlQEfQCMeq5xiMb08n6tPFzuEv3asYwqjGify8bXjmH9QvX5HlsgGnDpfpkaJS6J\n7kgMz7xz0tWYsvFSVIhQeJAgXCItopVlftuQj1UoJhs9kewMn1kBXkD0VtqPnNW139jcFMbOfacA\nAP/ja6WqfaOG6ePR0lCDUaU+XOyPy8V6zcagVNuVlYh1/LSJ0MsUknNJTLFu/jTVfRC9Iq/cI0vZ\n8VhSMkr7XwIEgzBbh2Eh3FKvuv2IVKVDmq8UNuyPuaswon0ubQfPgGWAbc31CAY8OH6uT9U1Wrpf\nRu1GlA05uy5E5DFFY+o2MW5/N4oVMloEkQbSxriR0Tl+rg8tbUdtc2O0PZGkygxOjR5gb/isCvBe\n6OXQNOsqVAR9KkNS6mXlBpHKQrxSOFRbYPa/vzKp1GFgfHXFbgXBtpST0fFmxwUDHgiCcRPKKyuC\nWPTLfapCuD3ROHbuO4XHv1+Lyy8tNS3xtO3ueld7QUbP5dxFDmDEf2tpO6q7X/1x3rappjQmJxX8\nh2ujSEfhQYZhljv5jCBGEkbydG3IxyoUo8yn6VyrqMzgYv/BrlqD2dv25LFl2HZ3PSpDfng8rGqv\nx+Nh5XFVjQnJ+0ZS6EwrMecFpB1KM63ewCUceakN08ejfcWN+MPPbsfeld/GhV4OZ/7UbxryNCqE\n23UhAkEAfrhtH/5h9xFdGC+dwsNWz8VtWoOU8ybNs33FjVg2u8p2fy3TSh6FiiPJO8MwHwmCMFPz\n2ceCIMzI2cgygCTvxFChVGcZVWTQvg2bqbkykTNbKcSyIZNWnt9Mwv53v+nAijlTXBfrFcOX6o7L\n6xfWojzgtcxv43kBvQNx9HIJlVx/453TEfR5dJ9vWDgdj73yX7jQy2Frcx3KS3yyJP93y25QeT4N\n08dj5S2puWSguLN6Lm5Ufckkj+6IXpYvvXCkO4YCJHPJO8MwTQD+bwATGYZpU/xTOYBu46MIYuQg\nvRn3cQnDkI8yFGMlcc9k/8GqL1M22rLLcxwwK3CbwMY7w4bFeu0WTalnl1RBpOt8Hx5/Rd3PymxM\nHpbFQ7sOqUKfK184iHXzp2Hja8fkvZ/TPVEAAi70cnhsQa2oxhMG1XjaavNtB89gz+GzOPbovIzC\naFbPxU0vrf4EL7ekkea5fGeHeH9sjFYue3blC7tZvAfgLIDLAPxc8XkvgEO5GhRBFCpmi7AT42CV\nhwPA8f6Dm7fndEv6GHUHTvI81i+sVXkwm5vCpuWNnNbAK/F5dJXxvSk5uhVSSxIl0t6VtPcjnevY\no6L6cffHn6MhfDnmbPw9ls2uwpOLZqJ3II7OtfNUSc3Z2Ptx85ysvjtcBRXpYvlEBEH4DMBnAK4f\nmuEQROFitwjbGQfLxUeAI48onWKoTt+2pYWz1MeK4SgDRaFSvXa6JwpBAHqiccPra4306PIAIlwC\nlWV+9A7EEfSJxX7TFQyYHSd6VlB9Jolj1i+sxeOvdCLBC+i6EEE0lsTf/eagYVJzJns/Tp8TzwsY\nSIg9vpQhUuV33d6fIgsJusapEGM+wzDHGYb5imGYiwzD9DIMczHXgyOIQsIu78Wu3ptVywil0ZNa\ndxgZAmmBUybiOsm9sWtHokxE7Tof0XUUXr6jA3OnjkPbwTOYu+kt/O0LHeASvGyIBhLW3Ypb/uob\n+OFWGYMAACAASURBVOfvTcWVFWI19mfeOYnuSAzJJJ+2YEA8Tp1c/Is7w7gk6FO3b2kMo2pMCNua\n67ChfVBmvvTmKvzdb/S1C6Wk5kwWeqf5c92RGM5f5HRJ38rvurk/wzWhWIlT3/dxAH8lCMInuRwM\nQRQymYZp7EKIRh6R8q1Z6rqrrWq+8bVO21I+dm/9ykXWrKPw5LFlcmKyVvq+pSmMEq/6jV4y0qPL\nA5g3bRwe2H5ANe6dH5zCvd+aiPISX1ohTNHQB+TcpyiXQIIXwCV41R7Z2t99Igswzl3k5OPN5hlK\n3XunaQdGOPldke65sjyV0XfdhHiHe9diwHlFjHNksIiRTqbN9Zx6UxLat2ajN/LVLx7CijlTLMdg\n9davrJYhLZxmVTJOdUfxk9uqsfq2aoNKIB06b09ZOWTFTv24F9RdAQZi7y1t6w9XhiL1VQFA63uf\n4rKyAOZs/D2ueWQP5m56C20Hz8jGaHPjoGemLAulnWemXoqT3xXpnpvdb+V3nVZtHwn7X06N1n6G\nYV5gGKYpFSqczzDM/JyOjCAKjGzkvbhpGaE1NmatOyZUBi3HYLWQSUbx+LnBhfOJN7p0eVeiR3cM\nD+06hK+VmlcC0c61MuTHhEr9uMeOCsDvZbG4Nf0wltaoL2k9gDtmXCEnOytR9iTb2lyHY4/Ow5jy\ngC68uH6hOM9Myx6VelmVgZTClMoeWpJhM7rf6eZTDfeuxYDzPK1nDD4WBEG4L/tDyhzK0yJyxVBu\ncmtbe7y7+mbEk4Ic9nrijS5RGt5cr5KZazHL1draXIclrQcMq10sm12F+741CaV+j0pVJynxfrht\nn+PcL6Prv7nqJlXDR7tzuJnX49+vhSBANZd7vjkRZSVe63wpLok1uw9jd8cZ+XxOKk+Yje3Xb5+Q\nmz52ne9D+5GzuO+GSYYpEGNHBdLKc9NSxF2LgSy3JmEBLBcE4U8AwDDMpVBL4AliRKArQ6QIr2W/\n99WgakzcS2Lw8EuD+0hSEq6tNNxsL03hgUnihJaGGkweW4bj5/rwZTSGxa2H9Ko1Lukq98vo+kbe\nl5swFs8LgABs//EslVH98NMejL+kFH/3G7HW4BWXlqInGsP9zx8wXMSVzxMMVHte8nwVbUycPmep\neryyw7OXZfA335ks/2y0V6XNc3PLcO9aDDj3tHTVL6giBjHSyfVbrfL8LQ01uuRlqUCs3SInyap5\nHinBQlJuIW/kqbQ01GDuprewcs5kNM6aoJK+S/MD3DWqTCZ5RFIS7d6BBKKxBFamlHuq+TisAGJU\nBHjDq52y4CIU8GIgnkQiKeB+Rb8wq+uYPc+KoE/XQNLuOfcNJOSCvqrrOnheIxhHfzROjdZBADcJ\ngvBl6ucKAL8XBGFaRkPMEWS0iKFgKDrJ2pVQsgtdJZM8uqMxU8OjXaTXL6zFhvZOnLvIyQt2f4LP\n+K1dulcbFtbKIc6+gQSee+8ktrze5crgm913bRX3Pi6BUp/HvLuxwXyMwr9mxt3qOUdjCfREYqpE\n7PULa1ER8iPoJ6NlQlbDgz8H8B7DML+FKNL5AYBH0xwYQeSNbO5JDYVSS1kmym0CLs8LiMSScs4V\noJdAq0JJqRb1UkkmuYBrqlRQJoY46PfI4otVuwYN6KbGMP765ioMxHndPo5p9RGT+y5VhldWkpAE\nJtr71tsvGsymWVepDKVU3STKJWWvlGVE4Yj2elbPucTnwYb2TlVH5A3tndh4Z1j1PSe/j9mqYThc\ncKQeFAShFcACAOcAXAAwXxCE53M5MILINtlOvBxKpVY6ysVoPImQSWdiqf6eSmpe4kXQ70zZ6JZo\nLIkVc6boJPsrdnbg8y/7AQbqhTiWQHeEM3xWUc46SVt5zfYjZ3XKvE2NYTz33knMnTrOJOGXG1Q1\ntu5HTzSGNX/5Z6rmmXYdgyNcAj//gWig/vaFDszd9BbOXeRUxzj5fbT6zkhIJDbCUXiw2KDwIGFE\ntsN5Q63UcvtWzQuCXL7IKJQ2Z+Pv5cTgUMCLEl9239a1yrxSP4vqNa8YhuokD0m6p1IStX5PqA4M\nwyAa05Y90s8BEMOfO/Z9Jqv4+gYS+NePP8fa332CzrXzUL3mZVWI1ex35MlFMzGq1Ifj50QVYNOs\nCeL1vHrv0Gi/bffHn+u8Oie/j9rvKCvQR7gEnnnnpErske3w9BCT1fAgQRQ92Q7nDbVSy23FbqWn\noaxesbkxjLW/+0SVGKw2YpkbXqPFe3NTGMtmV6kW2WuvrkCES6C8xCeO2a5KRMCLH27bh7GjAlg3\nfxomVAZx7qsBBP1e/OjZ/bqXh8qQH/d+ayKCfq9KZXj9pEo5qVcZYjX7HSkv8WHKT1+W79+ew2fx\nypFzlpVFgMGmm1ub63Rdhp38Piq/Y9aEs+tCRNcBeTjjNLk4bRiG8TAM8zHDMP9f6ueJDMPsS9Uy\nfIFhGH/q80Dq567Uv1+tOMfDqc87GYaZm+sxE8OTXITz3CQLDzVBnwdNs67C7o8/R0tDDTrXzsPT\nd9XhP89+haU3V8kNBceOCuDKimDGCbVKjKpwLN/RgXu+OVGXtGy0SFtV5Xj/RDd2d5zBTRvexA+3\n7cPFgQRKfB7Dih8syyDk96InEkNL21HsOXxWvm77kbPY0jQDpV5WrssotSvRXrfrfN/gPHZ24M8n\nXWZ4r8wMUchlLUqj75g14Vx6c5Xq+L4BfW3J4UTOjRaA5QCUJaAeA/ALQRAmA/gSwI9Sn/8IwJeC\nIFQB+EXqe2AY5hsAGgHUALgNwP9hGGZ4v0oQOWG4dnI1Q/IE77thEiaPLUN/PAm/h0HVmHK0tB1F\n9ZqX0dJ2FKvmVuO/v+qXj8vG27rZ4l0W8OLJRTPRuXawVUh/jJe/Y10lIoxNe4/pzikJHbSfG9Xu\nO/boPGxtrsPll5bgvhsmyXJ2aV8oGkvqKllI3ai11zS6V25ejJz8Piq/Y1YrsWpMmWqsz757MuOX\njkImp+FBhmGuAPBdiErDlQzDMABmQ2wsCQDPAWgB8CSA76X+GwB+C+D/SX3/ewB2CoLAATjJMEwX\ngOsAvJ/LsRPDj0JMvMy1+ksbUuwbSOgaJz606xAe/36tfEw2ekmZtdM4fr4PVWPKUL3mZVkGnuR5\n8Lyg60u28bVOOQQY5RJgGcYw+TfCJdB+5Cwapo/H0pur5LYpA/GkLC9X3gcpFFkWED0sZTjvsrIA\nBEHA49+vxeWXlsr7RlL4Tbpm1/k+NEwfj4fnfR2AmJfFsmL5JqeJ105+H5Xf6Te5p8p+YBte7cSe\nw2dVSczDjVzvaW0C8BOInY4BoBLAnwRBSKR+/hzA5an/vhzAaQAQBCHBMMxXqe9fDuA/FOdUHkMQ\nriikTq65EnJYNhQ0aZw4/pJSeFkmrc7GRtdnGWBzU1iTHxYGLwD9sYS8yGq7FBst5AIvoD/OY8e+\nz/T7c6kmlHf/xdXo5RKqvCijyvNatB5h1/k+BLysLAKR9pHeP9Gjyrf690/O4e/nfR0rFb24pAol\nFUGf4xcjJ7+P0nd4XtAZxM1NYbS+96lOjJHpS0chk7NZMQzzlwDOC4JwgGGYm6SPDb4q2Pyb1THK\n6y0BsAQAJkyY4Hq8BDHUZLONhNJQ9XEJPPuucdKueUPBhCrhVhAE9A4kEAp4EUm16PDYtHaXxiEZ\n4tumjsXTd9WhrMSLU91RPPq7T3DuIocNC6fjkX89ouosrAyx6bxDhTekbEIZjSVkcYMnweo8yGU7\nOmzvpfZ+PPFGF/7xr/5M7tC85/BZVI0OyfOQctkWzLxSVfFC8ljXzZ8Gj4dN+8XI6oXDyKCXelk0\nzbpKZVSHc8gbyK2n9U0ADQzD3A6gBMAoiJ7XJQzDeFPe1hUAJL/7cwBXAvicYRgvgK8B6FF8LqE8\nRkYQhK0AtgKi5D0nMyKILJItNaOZzFpSlSkNoVkdwpAiPyuZ5MXOxTsVnYsbw6gM+W0Nl9IQv3+i\nG7O/PlZXRmnVroNoaaiRjZZdOFJbI1FZuFeSqpt5kEG/x9rz1NyPC70cfCyLYNCr6NOVKmCbymUD\nxHQCo+tdWRGEy9q6Mk48byPPrNBC3rkmZ0IMQRAeFgThCkEQroYopHhdEIQfAngDwPdTX7sbwL+l\n/rst9TNS//66ICaRtQFoTKkLJwKYDOCDXI2bIIaKbKkZjZR6SlWZlSjBqKdXNJ7Eck3/q+U79f2y\njNAa4vGXlNqKB2yTpF2q7FTf4ZK2CbilPg/+ZfEsdPzjrfjVPfUoL/EhGPCirEQ05FKdRmXXZ7Pr\nne6JOn5+2m7S0Zh1t2Oz7tOFrGDNBUOhHtSyGqIoowvintWvUp//CkBl6vOVAP4eAARBOArgNwD+\nE8ArAJYKgjB8pTHEiCFbakYzj01SuCkXeGnBlcs2adY3nhdMq2iEHIS6tIu5eYPDhKNGmIB7lZ3y\nOywLywaY3ZGYqvpFhEtCEAaNg1llDlFwoe/FdWnQ5+j5GVWzsPMWR2L1CyOoIgZB5JFsqAfNKitI\nleHVBXI5VSUJSTwgKeqsqlFsba6Tv2c1H2WIa9nsKjReN0EVajQTm2RaY8/oO2BgWmg4GjMuhPv0\nXXVyK5O9K79t2vcrKFXfCAzWbTQSfmjHVeplUz+rE56teowByHlx5gIge1Xeiw0yWsRIwqz6RGXI\nj/44Ly/wVtXRLysXC8Iufm4/RpcHdJUXtHtaTg3MQMqjCQa8tgu7WyWlE0NmVSrJqnK+IIheoiTP\nd1td32xehka8MYyBBI/xl4gSeyMRjZXxddugsoChMk4EMRKwyvcpCwzuAJiFEZXigQ8/7ZEXRkml\n1x9LotTHwuNh5d5cEU5d+29zUxiVQdGoKSXaES6pM0QlXn34zEpJadSAURAE05YrqlJJZg0wU16S\nkZLyVHdULmn11KI619X1reY1d+o4eb8QAEaXB8Alefzkt2oZ/9LZVboXjkzGMZzIx54WQRAOMdt8\n12K0Ga/b6Depji6JB5T7UW0Hz2Duprew6Jf7AAayweqOxHD+Iqer1r58RwcisaRqfEYCEbMSUVqD\n2jB9PFoaalDqY/GFbk+Jw0CCl1uuWJ3bSnhitA+2fmEtNr52TD7nc++d1FXIcLPvqJ2XtqrF0pur\nZKm+8l72x3mVqGKkVXOxgowWQeQZM8OUyea70bFJnrcUD9gtjJIRurIiaCrUcFKHT2qLopyr0mBK\nCb0tbUfRdT5iYJw6IAhwnC5gpq7TGbTmemxo71RVv9jyehcqy/zY1myutrTCTphiVppJOw8nqs+R\nAhktgsgjVobJjaeixejYB7Z/hFDAO7gAN9ejIuRHeYkPLMvYLox2xWy7zvc5qsN3qjuqm6vSYCoL\nw5ou6gFPVtIFlAYNDAzLRPXHeFn+7lZSrn0RaD9yVuW5ne6JOp7HSJO2m0FGiyDyiJVhsks+tgod\nmh1b4vMMLsBS00dNrTuzhVFZzHaTQVHZ9iNnVYutk/Cbshq7ZDAnjx00VGYG8txXA7qCuk8umgkI\nYuJv70AcSZ43Daka3TtTTzOD4sHaF4H7bpik+nnMqIDO+x2pYT+njKwdPILIAtkscmtlmMxLLonX\ntFLbWR1rtHHvZE5KUcMrR87iqbvqUBYQZdtSk0PlYqsTiHBJrNl9WBV+0yY+S2WbpLFL1d6VSsYt\nTWH4PSyee+9TtDTU4JrRIfSnujSf6o5i0+5jcrkor0dMDu4bSIhVLRSNJo3uXS6qSxhVsShLqTCD\nfrGRZDrXzHWx5UKFJO8E4YJsF7m1lGRbGKZo3DjHSMrbcTpOMzWgk1wqUc4ullBSLprJJI9oyogo\n6xYazXXlnMm491sTxf0wTcdhpUz8nm9OFGv/Kb4TjYuqxu6IWkX42IJabHhVLMRr1NzS7t4VA0Pd\nNXuIoDwtgsg2Tlqku8Fu8TF7m+YFAStf6MCDN1XJ/aSefLMLG+8My3k7dm/itq3t05iTVd1ChmEc\nJB6HEQp4EfCyiMaSKmNmtBhbJVZ/d8vb6Fw7D9c8skc1J6v8LKf3Lt9k+/ewQKA8LYLINtkqcith\n11PJrHXFQDyJVXOrVa041i+sNe0hZbSQ2ba2T2NOyrqFAOS6hVI1DeVcI1wCS1oPqL67bEeHoXdk\nZjCsSlhJ4hDtnOxCp8XgxVj9HvZxiYI1ttmAhBgE4YJsFblVko4qjOehy+95aNch8LztoTJ2akCz\nOVkJQOzqFirnavbdKyuClmpJ5fUjqf0v7dhP90SxfqG647ByP9CJtF8rjonE7PPlhgqz38O+gcSw\nr09IRosgXFAoSZ6mxVUDzsdh3dreeE52uWNmRiTCJXTnMlt4jbwjs+s/844++fepRTNRWebH+EtK\nsfKWKbgjPF41J6fSft299XsLxhgY/R5ubgrj2XdPppUiUUzQnhZBuKQQ9juysaehDIONHRXAijlT\nUq3tk7LSzu113fTiMgrDrV9Yi8dfGUzw1c7JTswxEDcSlYj7ZNqah2bP0WyOGxbWoo9LompMGU73\nRDFmVEAOxeYDXSFeH4vqNa8Uc31CEmIQxHAlW/subg0wLwi2IgYz9aDt9bkkkjyPB7Z/ZDonu+s7\nNeamRYaDesGIVNQ2lhSwatdBlTGsDAUKZs9oGIgzyGgRRK7QLrYsC5T4MvO8XBuQND2+TDzFXC+M\ndmOzu74To2p1nqdTuWcA5HFEuAT6BhJY+ZuDBW0QikFAYoOjQdKeFkG4RLev07ofPZEYVr7QkfZ+\nRzp1BtMTcGTWTDAbe3pWQg67OdmKKBwKZcz2raT6iSrBiN+LsV8ryapqNBc4rU/otAhzoUKeFkG4\nxOwt/clFM/GP/3YUF3o50zdwuXOwpnHgUCW8puspOUkqdkI2vAG7Xl5Ozm+V3zV5bJluD6hvIIHF\nrYUXekvHOy9gb4w8LYLIBWZv6eUlPqy6tRpjRwUM38DFBYNTtXfvicTQOxDPev6X27FbXUfrnf3o\n2f3ojycBAa4Lt2ZSBFjCyhszqtweCogdjJVeRdDnweYm6/qJSo+EZWFYI7DUy+bNa0nHa87G/c83\nhRGMJYgiwiw5tet8H1rajmLd/GmGNf7EBUOdePvQrkNYN38aWJZJu8mfm7dttzUJpXHv2PeZ3BSy\n63wfduz7DPfdMMn92IbAOCubUPbH9U0oJa+iMujH03fVIWRQP9HII3lq0Uxsa66XPcxSL4ueaDxv\nXotV40yz5zJUL0e5hDwtgnCJ0b7KYwvERNYPP+3BhMqg4R6PVefgoN/dXpHkBSR53qBJovnbdjp7\nUqU+FnfMuAItbUdRveZltLQdxR0zrkCpz3r5MPIE+gaM87jSSWS2w86r8HhYlAW86I8nMXlsmVyB\nnWUZ09YuYCB7eP0JPq9eSzoGKBfJ8UMNGS2CcIkUgtraXIfOtfPQ0lCDDa+KuUXXXl2BKJcwfNM2\nWzBO90TRH+cdN/lTGgPjJoniwmm24IcCHlVPLTvPIBpLyv2tpGusfvGQ7UJntPA/++5JXVgu3URm\nO5ws6mahRifH5ttrSccAFUpyfCaQ0SKKlnyqoFhWVJX1RDi0tB3FnsNnUwtA2DThVFwwzDsHGy2g\nRnNUGgOrzrfdBm3qewfi+NGz+xH+p1fxw237xL0pG+xKM5lhtKhveb3LsXHOdP8lE6/CybH59lrS\nMUDDoQMy7WkRRUkhqKDEBSDguBeS/H1pX0ShHrTyqHRzLPPrmiRq96ikqhBGxWjd7IEA6e2DWR3X\nH+ctC/lKZOrJKPt/Ke+fE69COnbHvs8wd+o4VI0pQ4RLoNTL6r6TzvmzgV2xZbO9TrtCyoUOSd6J\nomQYZP/bYjbHrc11cnX0hunjserWalWTxM2NYVSE/Pj6P+hL+ihbdUif2ZX5SfcFIZ3jlAtthEvg\nmXdOYuPe46r5uy1VlW4idTLJozuq7tWlq9BRACW9jCiEl7o0oNYkxPAl3/sJmeKoU7DFHDc3hbF8\nRwf2HD6LqtEhPLWoDmUlogpu5wencO+3Jhp6Oad7oqrzOfGY7N7os3WcYWmlxjAAMayYjieTiVfR\nn+Dl/ULA2DMtVK8lHWVhsVDcoydGLOmGrAoBp2/BVuE1Sa5dVuLF8XN9+Id/OyIXmfWyDP7mO5Ox\nfmGtqt/Wz38wHUG/B9dPqnQdzrJanK0MsJtF3WihXb6zA08umomlsycjGksg5HeXF5YJxfxiVMxj\nt4OEGERRkmsVVKYiD6vjnQoMrOYoybWjXBLtR85i6c1V+MPPbkf7ihuxbHYVolwS5QEv1s2fhs61\n87Bu/jSE/B6UB7xZ3YTPVOGnmq9F0nb1mpdthR/ZJt9Ci0wo5rHbUdivpARhQrohKydkuh9gd7zT\nt2AnXY29LHQt6zc3huFlgaDfB4+HBcMAl5UHBhWKqYrr6Xqkqn2nWAI79n2WlTCUVdL2tVdX4FR3\nFKGAd8j2ZfIttMiEYh67HSTEIAgNmYo87I7PpojEtCZecz3KSrL/TmpkkB9bUCvnqQHp93AyO/fu\njz/HHTOuwIZXO1E1OiT3zpKMOICsiiGyVWcx3xSqSMQCEmIQRDpkLLW2OT6bb8HZ6GBshXbhgwDd\nvtPqFw+hpaFGNlrp7i1qPcsIl0Cpz4O5U8dhw6udAIA7ZlyBJa0HVKWVYkle0/QxfZWcmZcc/P/b\nO/8oqcozz3+fqv4B1eCO/FyMv9PITlBshaPJMeuKMZIw53ScEDMwUSSbjUkWV1jHrMnEc9Ink0yG\n6LDCrmcUo+NgZsBkzDE9uzoYo45O1pBgBJTMwbSYIIEjCEbpLrq6q+rdP6pu9a2qe2/d3/e91d/P\nOR6b+nHve9+qep/7PM/3fZ6urPa50kZ0FYkEhTktQhoImg9o9f4wN3hGmbuwylfZGcneOdNCyS2a\nN1iLCG588OdYds/zGNxzGGuX9jZV5ngnP17bjxZGKaV2KCjb7tBoEdJAUJGHm/f76YUVxVidsFrA\nDx7P2xjJomsD7Fbk0nhtVtU/zpqRC1UlN7Uzg4H+hTVRS//FZ7SN6q5daB+fkZCQCCryiFIkEue5\nrMKc9zz9Gjav6msKx/V0TRhgJ7yIXKzChY1CjTdP5EPb+mCMbWBwX11OrXd2Tyq2UkwWKMQghFhi\nJxh5cM0SlBV8GckgIhSzwZt7WjfWX3MBzp6Zw/BoEQ//9I26Dcgze7oAeBNo2I3t/hsX+/aGUyiG\nSBIKMQiZbIS5SNoJRsy1Er16H0FELobn9eCaJbXaijWZ/6o+rL26F6fGy7XQqNdtC3Zjmzalo2WZ\nK6s5d/IqgXAVj63G0k4wp0VImxDmRl8gmorgQYUjmYygrNAkvli3bXetEK9dP6xWggo/Y3Oac7sx\njBZLrj4nrxvcw/78dYVGi5A2IQrlW1iCEYMwhCNR9bryMzanObcbQ7mMlp+THwM0WZSPDA8S0iak\nod5cGMIRN3Un/dSmdDs2cwguA+A7n1qEM/5gKoaODuPeZ4fwxCtHau+3GoPt3jrT5+Sn4G0aPv8w\noKdFiGb4rXuYlnpzQb03Nx6RX4+u1djMHtBtj+7GifwY/sc/7sWCO5/EwOA+3H7tgkrtx6rBsxpD\nvtD6c/JjgNLy+QeF6kFCNCJI3cO09VAKIhpw894oyjGZFYY71l+JgcF9jmpDq3ECrUUiflSWafv8\nLXA1SBotQjQiaF3CtKjH4lxgwzxXWSlc8LUnUSwrvP6Xy7HgziebGm26qbvY6nMK0njTykim4TsB\nl0aL4UFCPBC0ZUkrnMJCbs4dJPRmd/xW5/UzJ3GKBsI8lzkEZ1SfN+M2HNfqc/Kr3Gw8LoC2UxTS\naBHikjgkxXZ5idFxdzJpv9hdW6lUdjyvmzmxMmpxigbCPJc5T/U3zw3hrusXRdbTze0NSBi929IE\njRYhLoljAbBL3ruRSQMBRBwO1+Z03lbP2xk1N2KEsAhToGD2gDb+SR9m9HThgdXh7WPzSqubhnZU\nFNJoEeKSOBYAu7CQG5l0EE/Q7tp6ujuc26y0mBM7o5bJINLO03XXFnJRYbMHlOvqqFXMsFMb+g0n\nu3lvy5uKNlQU0mgR4pK4FgCrsJCbcwfxBO2ObxSptTtvq3HZGbUpndnQq23YYXUjMCPXifx4KbLc\nJBDsJsLte932bovj5iAuaLQIcUmSC4CrvUkBPEGn4zudt9XzTkYt7GobTtR5R51ZnMiPRy5OCHQT\n4fK9cfZu0wVK3gnxQJKS8lbnjkou70aebfe8jnuHgs6TW8zyeAPXkniX741qfhP6nrPKOyFhk2QL\n81bntqvK7tYTtDt+q/M6PR9nbzG3tPJIw1qw/ZSS8vreKOZXxxsNMwwPEtIm6BoKijMM6AankFqY\n2xqChJO9vDfs+dVdJs/wICFkUuHkSeTHS6GGDqMuVRUFQcKaAWF4kJAwiWIRCXpMXcs26TouwDmk\nFva2hiDh5KRC0UHCmnHA8CAhLoiiGobTMd3s0dG16Z+u4zJjF1JLy76mKMuJ6S6TZ3iQpJq47uij\nUJxZHfO2a+bjsx8+Dz3dHTh4PI97nn4Nb71XsEyEx6GCM+Z3amcG+bESero7MFIoIteVrbW2b5zv\nuNR5UVAqlXE8P4Z123ZrKUIAnMObQHNxXKvH3HQM0FU9SE+LpJY47+ijqIbReMz+i8/AdZeciZu3\nvoQLvvYkvvrDV3DbRxdg9vRuy0S4mzEFrchwfGQMD71wAL97Z7Q2rpu3voTfvTOKh1444GvDq1+i\nLlZcLiucyI9j+86DGOhfiP3f/Djuv3ExZuQ6tTFYgL1QYrTYXJ/yvdFxHB8peP6N6CaeMUOjRVJL\nrJXCIwgbNR5z7dJe3PHY3rrrueOxvVi7tNdy0W81pqBG3ZjfZRfOsxzXsgvn+drw6ge/hXm9YFzv\nxqd/jWX3PI/3//kT+MIjL+FUsex73FFgd1NgVZ/y9/lx3Lptd+i/kahvIJyg0SKpJdZK4S3i/H5+\nxI3H7J0zzfJ6eudMs1z0W1ajCGjUjfl1GpfVfEeRE/FbmNfLYpqW4rJ2NwVW9SnPmpEL/ZqS4VSA\nEwAAHIRJREFUzlnqHWAmxIE4VU5OijO/mzEbj2nU+Wu8njdP5C0X/VYbS4Muwsb8Gn2jGsdlPB7H\nhlcvhXkB1Iyalzya7qo5A7tN5EblfPP43zyRD/2awpjrINDTIqklbpWTreLM9CNeftE8DPQvxIye\nLoyMtfa4zMfs6eqwuJ4+zDmt27MQoFxWGCkUsf+bH8eO9Vei/+IzAHgL0xnzu+PVI9iwor5v1IYV\ni7Dj1SPxbXj1WZjXi0ehu2rOwLYTQFfz+Hu6srj7+otDvaakPVKqB0mq0aUW4K/fGsaLr7+Nq//D\nXNzx2F7fyjMv12Pn4c3IdeJEfrzu8Q0rFuHxlw9h1eXn+BqPF/VgFFhd6303XIpsJoNcd8VLvXnr\nS4EVizrvL3ODefzDo0U8/NM3cODtEay/5gKcPTOHfKHyXJBrilAd6mpQNFqE+MBqEb1nZR8e/flB\nbHz617XXRSn1tls8tqxebLmAb1m9GD1deinBDNwYC/NrRsdLGCkUcWtVmn7r1b1YednZWLddX6l6\n3ERlgCOsTciKGIREhVVcf/323RjoX1hntKIoxGrgtXFjTzVcpxtuF0Ej5FguK5TKqqaKA1Cb8y2r\nF6OnuyOVXlLYRFVRI+kiyMxpEeIDO4PRO2da3WNRFGI1lIp2LetbNW7UDS8qx3JZ4eTouKVh3vzM\nUM0w67a3qN1Ich8XjRYhPnDq9GuV9A5rT5nZ+N35+Cu46/pFludLg6DAwEtif7RYwslCEQeP530Z\n5qD7i+LY4JzU/qe0wPAgIT6wkx33dGUjLcTaGJYsK+Dbn7yokmQ3nU+3HlZOeJGal8vAl3+wF7On\nd2PDikVNohcnwxw0FxPk/W5zdjr3sdIFCjEI8YnVQgRY13mzVVytXgIIXBuVBNtGNI8lpBydl8Xa\nfP39F5+BtUt70TtnGk6NtVbFBVW9+X1/q+sz5hEK+PzWdNZsDAnWHiQkShrj+gCa8lZvjxRQKpUt\nQ3Z3Xb8Idz7+iqf8li5VyMPM0WUyghm5TmxZvRivfevj2LLavt6fOY83uOcwlt3zPG747s7acZwI\n6u36fb9TaNg8j1NTUpEjaWi0CAkJq8Vp3bbdGKkaFPOG0G9/8iJ855/34/Hdhz3lt3TJV4VZ99Eo\nVGsuyHsiP25pACsbaPuaNmC7WdhtDX6h5Cp/5JTHdMpBORk78zwaFUaaxqepgCYpaLQICQknCXp+\nvFQnQb5m479gcM/hute5WXhr+arV1WoIq5egpzv+O/EwqyLYGkCLxbpy/d0N1SC6XYUlg3q7Vu/f\ntLIPf/uvbzh6m07esXke7312qKnyiM4CmqSILFAqImcB2Arg3wMoA9iilNokIjMAPArgXAC/AfBp\npdQ7IiIANgFYDiAPYI1S6pfVY90E4M7qob+plPq7qMZN9EbnigV2goKho8OYP3day9d5qQd3aryE\nz2/dlVjCPsw6fbYGsDuLclk1XZPf/UeNApW33h1FWSn89af7MHR0GNt2/hb/+T+eb3tMq1qRf/uv\nb9T2iNnV4LMT7eQ6s3XzaNzEWAlryARRelpFAH+mlPpDAB8EsFZEPgDgKwB+opSaD+An1X8DwMcB\nzK/+dzOAvwGAqpH7OoDLAVwG4OsicnqE4yaaknR16VbkOrPY1BC6Mmr0mb2GoCG+OFuy2BFmmNLO\nEzl4PB/6NRkGTymF8ZLC7T/YiwV3PomBwX247pIzMbXTeUmsqxXZ3YHNzwzVPW/lbdrVCsxkpGke\nj50soKe7A1AIff9Tu8jpY1MPisiPAPzv6n9XKaWOiMg8AM8ppRaIyP3Vv7dVX78fwFXGf0qpL1Qf\nr3udFVQPtidp6IhbKpUxUq3RN3R0GDtePWJZ7y+Ix+hXQRi2l+p0PC/nKpXKOJEfq5VkMmolbvzx\nfmz8k75IVJEnR8dtS11Nn9Lp6hjm76NZyZgfK3oqlxVH9CAlcnp9yjiJyLkALgGwE8BcpdQRAKga\nrjnVl70PwJumtx2qPmb3OJlkxF1d2s9iks1mMK1bkB8vYf7caXjf6edbvi9IiR0/obkoFi2rayiX\nVWWuurN4+2QB9zz9Gt56r2AvYa+KMIz9ZmfNyGHo6DDufmo/jp0sRNYWxKnUlVsML2nbzt/iukvO\n9F0oOapyS2aSbicSJpELMURkGoDHAKxXSr3n9FKLx5TD443nuVlEdonIrmPHjvkbLNGauOTelYW3\n6KtNeRz4Cc15ETv4pRa+3VqZs6/+8BXc9tEFmD292zZ8aYzrW//335ARwQ3f3Yk/2vwCjp0sRCpC\nCOO7ZIT9Pvvh85o6O8cdrm1F0u1EwiRSEysinagYrL9XSv2w+vBbIjLPFB48Wn38EICzTG8/E8Dh\n6uNXNTz+XOO5lFJbAGwBKuHBEC+DaIJTQjssjIV3pFDEV3/4iuc70zjCMH4qXngVO/jB6m7+jsf2\nYqB/If5o8wuWC6QxLiPUOdC/0PVm4SD4+S7Zed52XptOBiEtDS7dEJmnVVUDPgjg35RSG01PDQK4\nqfr3TQB+ZHp8tVT4IIB3q2HEHQCuFZHTqwKMa6uPkUmGU0I7LIyF12+b8rhEEl4Lltp5FsdOFirN\nKkNIzjsVEbbzYszjqtssLK03CwfB63fJSQTkd/9WnOiyvy8MojSxVwC4EcArIrK7+tifA/grAN8X\nkc8BOAjg+upzT6Aidx9CRfL+WQBQSp0Qkb8A8Ivq676hlKr/ZZBJQ9Txf2PhtWsx3+rOVNcwTK4z\ni/tuuBTv5Mdx1owc3jyRx+m5TgwXSrh560uheIV2d/NvnsjbLpBxeM92ePkuOeWErK7B2L+1+Zkh\nLUQPrbxznbeSNMLagyTVhP1jMxRhs6d34/ZrF7RMrjeeX9f6ceWywtsjBawzKfTuu3ExvvhI8G6/\n5nM0h0b70NPdgSkdzh2YdV8wWyk26xpUjpXw7qlxzDltCoaODuPeZ4dw7GQh8e9AI1ZdjhM2svqo\nBwmJgijyR+a75o0/3j+x0dOiTbldC/jNq/rq5NtBPQcvi7rda/PjJawzNU188cBxTAs5F+Ml11Y3\nzvHq60w1HL0Qh9FrlRMyN6gcGSvitu/vaZLvJ+1tm7H67m5YsQhDx0YwuOew1spCeloktUS1b8vt\nImh3/gfXLEFZIZRF1FMFdIfXQtDkKexYfyUGBvfF7hWGebMR1/4jt+ex+058+5MXYdb0bm2MgN04\nB/oXYtk9zyfVOYBV3kl7E1X+yK3Iwe78Uzqzlu/3U5HAjbCj1sl4zP61VmKBHa8eaargEUc+KUyx\nSpzCFzfCDbvvxNkzc1qJHlp13ta5UC+NFkktSbfp8HJ+vyWoWhlmt60trNRjqy4/BzNz0aox/VxT\nXMfyehPh5mbGqZK8Tnk6u3EOHR3WXllIo0VSi3khvq7vDDx3+1X4+89fDijEIjH2IiP26xG0klOP\njBWxbedvW7a2sPMUKhU83Ennw6pdF+bNht9jRVXH0vY7oUE+y/z5ZQRNLV42repD75ye2G5e/MKc\nFkk15bLCaLGEkUKxSfwQxw/Pbf4rSL3AxlzKppV92P7zgzWl14YVi3D3U/sBwJXi0e916piH8nos\n8+d18HgeG3/8Wq26elj5PB3VkHaioWwmg1y3NuN0dXIaLWKJjj88O9JQSDfIGM2fRWM7DOM4RgK9\n/+IzcNtHLwi9tUXYcxzm98v1jYONYu7up/ZjcM/hpMQHsZCG3wgoxCB+0b0FSCO6bug1E6QigZt2\nGL1zpoXa2qIxFDi1MxO6PN5LRY8wjmUVor3jsb1Yu7QXQCWsODyafPWKKEjDb8QtNFqkCR36NXkh\naUGGW3q6s3Udh2f2dAGApzyR/bUWa7mqGblO5MdLvnNPdjctt17da3FevebYCSfFnNH77OGfvqHt\n9zwIQX8jOvXiotEiTaTtrkz3umqGEfjcw7vQ942n8JkHduLUeAlKefdop3ZksGllQwJ9ZV9tc26u\nM4sT+fFAXrLVTcu6bbux5orzGua4DxmJR/QSBnYL96mxEgb6F+Lup/Zj8zND2n7PgxDkN6Jb5IU5\nLdJESuLfdeicgxsuFPHCa0fxoffPwmlTO/HeqXG8+Prb+PD82ZaNCJ3mebhQxEMvHMCyC+ehd860\nWqNJo018GJ+dk2gkX6j0yjp4PN+yV5arc8X4uVnltO66fhG+88/7Qxdj6IjfuY5xPWAZJ+KPJIuY\n+iWORnp+mdKRweJzZuBL3/tlnQKwsaWF0f0215XFcKFouajkurLY/MxQnRCjIyO45SPza8/beclu\nFy2nkkUQ4DMP7Kx7zm/Jn7i76TaVmSqUUCqXcexkAR0Zafk91/nGyA1+fyO6RV4YHiRNxNECZDJx\naryEddt314fbtu/GSKFYC1f1X3wGbr92AQYG9zmGYOxCXIaAwO750fFSU4jn5Oh45X0NeQqnUJLd\nAja1MxNJtY+wqRNtTOnA9Cmdrr7nuoXI4kS3nDGNFrEkTHXXZMepSeCGFYvwofNnYu3SXlfdb3Od\n2abSS2YBgZ3BKZdRZyCWLZyLQrFc6zJsXoSdblqsFrBbr+6NpNpHENwKB4IoD8MwsDoJHOzQLWes\nVxyFkDbE8Kiswm2Pv3wIA/0LMX/uNFcLuGFQjA6/Q0eHcfdT+/HEK0dwy0fmIyPWldYhqB2//+Iz\n8MeXnIkvfm8in9bYmdkcSsp1ZmthMSjgvhsuxRdNoc41V5yHLzxifyw7ouqmG0n1/wgMrN9xxh2m\n9NMpO0roaRESMbnOrKXib2pHFqsuPwcDg/vw67esSzCNNNx9GyFAw2Dd++wQBvccrgvXWHkPZg9p\n7dJeTJviri1JU1hs6y6Mlcp4cM2EF+b2WFbzEsUdfBReURQhMj/jTCpMqVPkhepBQmKgVCojP15C\nT3cHRqoii2w2U7trntqZwfGRsbomjRtWLMLjLx+qFLat7umyquhgfo3dYlIqlSvH374b3/svl2Po\n6LCrtiRulGNhVfsI6w7eb8msVuMM23vzM840Kns9QPUgIbqQzWYwPVsJbEyf0ll73ByGm9XTjS2r\nFyPX1VEL+w3uOYwXD5zAAzctATCRlwJQq+iwZfVi9HQ53/2eKpax/ecHMdC/EKfGStjx6hFsWLGo\nrk7hplV9TV6Om7BYELVpFKrPKMKOYYbIDEMNBc/j1E3JlwQ0WoTEgBuPIpOplGlqvPs2L0pWC1ZP\nNWzjhFkqbygVjXxa75xpGCkU0dPVPCY3BkC3nEcQI+r0OYVhYM0e29zTunHX9Yvw5R/sdT3OqPKA\naWJyXCUhCeIltGS3KI0UihCI5XOj46WWnZLNxzU20poL69rlKdwaAJ32yfk1onHsGzPnsQCgrIBv\nf/Ii1wWO07iHMmyY0yIkYrzkIZxakRx4ewS3L1tQd2d+3w2XYqxUbtmWJciCnPZNtW6JI19k5LGW\nXzQPa5f21gQ1vXN6kM2408W18efBnBYhOuAlD9HoJTS2Imm8M4cCbv3eL1vKzYOE8HTyooDoFu04\n8kX5sRJuvboX111yZlM+cVZPdyo/j7ih5J2QiPEql3ZqRTK45zCu2fgvMCIkuW5vBlEX2bJfopR8\nx1H5IdeZxZorzmvaSL5u2+62rC4fBTRahERMkP1Ixp35jvVX4vW/XI4d66/E/1rVV1u47fZ3pall\niBeiLP0UR+WHTEZ872sjFSafb0lIzAQJzU3tyGDlZWdj3fbddaGk7TsP4sUDx3Hvs0NN0vV2TsxH\nGcKLSwVJBWAw6GkREgN+Q3OniuXmYrvbdmPZhfMAVMKFdz+1HwP9CxMpbhx37byoQ3jmz8koX9Xq\n2rzOgW61/NIGzTohGuPUbddgcM9hHDtZiL0qQtytRYD4JN9ur83PHOi2ry1t0NMiRGPsPIuRQjHx\nO3Vzfmn5RfMw0L8QM3q6MDLm3ePyUpU9jrY5bnNnfnNsdp53Gqq+Jw09LUI0xs6z6OnKJn6nbniB\nRoWNxryaW2Pi1VvxKvn2I5F3mzvzmmNzGksSnmsaoadFiMbYeRbZbCZx+brhBbrtBWZ7nAgVgX4l\n8m5zZ15ybK3GkkRTzDRCo0WI5ui6v8rwAnvnuOsFZnucCBWBfg2BW7GEF1GF7VjGShguFDG1M0Mp\nvAsYHiRkkmBug5Ifq7RJCRJaNLzAkTH7JpduwndRSsDtDOLUzgyGC0XbkKFbsYQXUYXtWLqyuOG7\nO7FpVR9uvbq3Vv0kzHmwIq3loOhpEeIRr8lyHZLrRmjqoRcO4HfvjOLmrS+FUlEikxH0dHUEknBH\nKQG3Ct/denWvq5ChWw/X6nVWn7ldKHHo6HBtK8OaK86LRWCTVDPJMGDBXEI84DVZrkty3SgGO9C/\n0FXzR68EvWuP6q7fav7vv3ExvvDIS5EVxrX7zGfkOnEiP97UxNPom2Y0gMyPRe/9aNpMkgVzCQmb\nxtYSdgVq/b4+KozQVND8kx1Bi7hGVQTWMnwXcg6t0eBmpLlZp/GZm8dy8Hi+ZrCA5lBglN+PNDeT\nZHiQEA94/bHrsjiMFIq1UNRkqlUINIfvwqyqYRVmGykUMfe07rrXGZ95zTgroKe7A8dOFhLZaxdH\nceCooNEixANef+y6LA65riw2rFiEHa8ewYYVixLfmJwkYebQrBWBu7H+mgvqXtf4mce1SdqONJeS\nYk6LEA+kOaf10AsHsOzCeXj/7B4MF4o4bUonRsaK6OnSR0YfF2Hl0IymjkWTgMHITX3mgZ1abxLW\nUD3o6uQ0WoR4xOuPvVQqIz9ekZiPFIrIdWaRzcYb5NDFeLYbtoKG1UsAgU4GIQ3QaBGSNDoZCw3v\nrEMhyevS4fNto8+VRouQpNFUWtw2THajocP1h4irAVOIQUiE6KIebBcaN+2OFpOv15dkma3JWK+Q\nRouQCNFFPdgOeJWXTwYm400RjRYhEZJmabFu+JWXtzNJ3BQlXZaMQXVCIoRdasPDzqs4e2YOHzp/\nZqSdjJOiVb4srk7O5vEknUOjEIMQkgomm7zcrYGIUwgSsbCIQoygJO0GE0ImsA21dmW17DcWlFYi\nC2N9qi31CpFfvw45NIYHbdDBDSaETDDZQq1OBiLK9cnJc4uy95lb6GnZMBmlpITojq5dnKPASWQR\n1frUqs+WDsIielo26OAGE0ImL44iC0Ek61OrVjo6eLs0Wjbo4AYTQiYvTgZiuNpqJuz1yc3NelS9\nz9zC8KANOrjBhJDJTSYjyHVONK/Mj5dQLqvI1qc0bIan5N2BNipESQhJIU6CCwChr08JC9BYMJcQ\nQnTBz01wEgWXE7xZd3USJmcIIakjbVEQvx5MEoKwpHNWrWBOixCSKlrJsnXEr0Q9DTmmuKHRIoSk\nijTuofTrMVEQ1ox+vh8hhDiQxj2UfrfQ6LAvSjfoaRFCUkUaQ2ZBPKbJVAXEDVQPEkJSRVrrgqZN\nPJIAlLwTQtoTGoC2hJJ3Qkh7orssm0QHc1qEEEJSA40WIYSQ1ECjRQghJDXQaBFCCEkNNFqEEEJS\nA40WIYSQ1ECjRQghJDXQaBFCCEkNqTFaIvIxEdkvIkMi8pWkx0MIIUlRLisMF4ooq+r/NW7LEjap\n2EouIlkA9wL4KIBDAH4hIoNKqV8lOzJCCImXtNZeDIu0eFqXARhSSh1QSo0B2A7gEwmPiRBCYieN\n/cTCJC1G630A3jT9+1D1MUIImVSksZ9YmKTFaFn5vHVBXBG5WUR2iciuY8eOxTQsQgiJlzT2EwuT\ntBitQwDOMv37TACHzS9QSm1RSi1RSi2ZPXt2rIMjhJC4CNJQsh1IhRADwC8AzBeR8wD8DsBKAH+a\n7JAIISR+MhnBzJ4uPHDTkknZTywVRkspVRSRWwDsAJAF8JBSal/CwyKEkESYzP3EUnO1SqknADyR\n9DgIIYQkR1pyWoQQQgiNFiGEkPRAo0UIISQ10GgRQghJDTRahBBCUgONFiGEkNRAo0UIISQ10GgR\nQghJDTRahBBCUgONFiGEkNRAo0UIISQ1iFKq9atShogcA/DbEA85C8DbIR4vzXAuJuBcTMC5qIfz\nMYHbuXhbKfWxVi9qS6MVNiKySym1JOlx6ADnYgLOxQSci3o4HxOEPRcMDxJCCEkNNFqEEEJSA42W\nO7YkPQCN4FxMwLmYgHNRD+djglDngjktQgghqYGeFiGEkNRAo1VFRD4mIvtFZEhEvmLxfLeIPFp9\nfqeInBv/KOPDxXzcJiK/EpG9IvITETkniXHGQau5ML3uUyKiRKRtVWNu5kJEPl39buwTkX+Ie4xx\n4eI3craIPCsiL1d/J8uTGGcciMhDInJURF61eV5EZHN1rvaKyKW+T6aUmvT/AcgCeB3A+QC6AOwB\n8IGG1/xXAPdV/14J4NGkx53wfCwFkKv+/aV2nQ83c1F93XQAzwP4GYAlSY87we/FfAAvAzi9+u85\nSY87wbnYAuBL1b8/AOA3SY87wvm4EsClAF61eX45gCcBCIAPAtjp91z0tCpcBmBIKXVAKTUGYDuA\nTzS85hMA/q769z8C+IiISIxjjJOW86GUelYpla/+82cAzox5jHHh5rsBAH8B4DsARuMcXMy4mYvP\nA7hXKfUOACiljsY8xrhwMxcKwGnVv/8dgMMxji9WlFLPAzjh8JJPANiqKvwMwB+IyDw/56LRqvA+\nAG+a/n2o+pjla5RSRQDvApgZy+jix818mPkcKndR7UjLuRCRSwCcpZT6P3EOLAHcfC8uAHCBiPxU\nRH4mIi0rHKQUN3MxAOAGETkE4AkA/y2eoWmJ1zXFlo5QhpN+rDymRlmlm9e0C66vVURuALAEwH+K\ndETJ4TgXIpIB8D8BrIlrQAni5nvRgUqI8CpUvO8XRORCpdTvIx5b3LiZi1UAHlZK/bWIfAjAI9W5\nKEc/PO0Ibf2kp1XhEICzTP8+E82ufO01ItKBirvv5A6nGTfzARG5BsDXAPQrpQoxjS1uWs3FdAAX\nAnhORH6DSrx+sE3FGG5/Jz9SSo0rpd4AsB8VI9ZuuJmLzwH4PgAopV4EMAWVOnyTEVdrihtotCr8\nAsB8ETlPRLpQEVoMNrxmEMBN1b8/BeAZVc0wtiEt56MaErsfFYPVrnkLoMVcKKXeVUrNUkqdq5Q6\nF5X8Xr9Salcyw40UN7+Tx1ER6UBEZqESLjwQ6yjjwc1cHATwEQAQkT9ExWgdi3WU+jAIYHVVRfhB\nAO8qpY74ORDDg6jkqETkFgA7UFEFPaSU2ici3wCwSyk1COBBVNz7IVQ8rJXJjThaXM7HXQCmAfhB\nVY9yUCnVn9igI8LlXEwKXM7FDgDXisivAJQAfFkpdTy5UUeDy7n4MwAPiMh/RyUUtqZdb3RFZBsq\nIeFZ1Rze1wF0AoBS6j5UcnrLAQwByAP4rO9ztekcEkIIaUMYHiSEEJIaaLQIIYSkBhotQgghqYFG\nixBCSGqg0SKEEJIaaLQI0QAROdeuQjYhZAIaLUIIIamBRosQfciKyAPVPlRPichUEXnOKAklIrOq\npaIgImtE5HER+ScReUNEbqn2OHu5Wqh2RqJXQkhE0GgRog/zUWnrsRDA7wGsaPH6CwH8KSptMr4F\nIK+UugTAiwBWRzlQQpKCRosQfXhDKbW7+vdLAM5t8fpnlVInlVLHUGmV80/Vx19x8V5CUgmNFiH6\nYK6UX0KlNmgRE7/TKQ6vL5v+XQbripI2hUaLEL35DYDF1b8/leA4CNECGi1C9OZuAF8Skf+HyduL\niZAarPJOCCEkNdDTIoQQkhpotAghhKQGGi1CCCGpgUaLEEJIaqDRIoQQkhpotAghhKQGGi1CCCGp\ngUaLEEJIavj/4UM/kky0lUQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5012a90bd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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qvHz+cLr30pjSdN5U2aG1i7BlaXOgEyGOAnIucraLjOX4nPwzloOc5v1DtntL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\n3Y5ATygtADakBcBG5nKRqR1wBQkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f500918dfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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eIScMjpB1N1Qny/udCy4PfH8d72gfu+Bi0dUXj9g3Yhdc9vw0ZtWZrggjBJca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\ng40WERHFBhstIiKKjf8fo6/qUyK0u+EAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50093ee9d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RZeTqbXt48Ma+tC9N+SWUaiG//9hOkflIzzNMK2Zb5suJyCO7/VvrMlFkOTgiU6UFh2uZ\nxrbHljCxS16QJRcXS0fyZiotVauMI0SXkBxigvrk98LPD7U03Hvh54dEeCtqcbFyIiLZzzSt+VK3\naTGKOZ+rz5/BwzddzJSeLO+N1PhW/5siJj6otzaff+Y0bntsZ0sdmoTW5qVqyFO79rWE0J7atY9b\nLj+LyY7bAam9mLsUsz5/cdPFbWUmEjYcaZ0iddGKUa2FLDr/tLZJvVoLKQioXh+phWx8dm/LxL7x\n2b31id3xvF0x67P0o7M5VKoBkM94LP3obBGTg3SCIGIkCFvyyJmM289jnGoYcdfm3bEQmoxcZFq+\nilpcHGOwXOMbP/xZmxVQfbfudl4EIIwi3jxYbstpnX5SAd9xKVpd8l5h5Yb+lslhem/e+ROJ5I7T\nQRAxUGp3oZlWzIlYuCQXhpcqAQOlDp3ei7ljdbHX4uKjpZjzuX7+GS3mndfPP0NMeLBUDblzU2ud\n1p2bnhcUX+8fE1/vF5GPlJxrHQlCVm1svW+rNvYzIqTgXbIQo5Dz+acX327Jkf/Ti28n3jJHF60Y\npWrIHU8+1/IGuuPJ50RM6lB3/JgxJc+226/klS9+gm23X8mMKXkRjh+SJwfJY5PuQiNZiJFWV2Zd\ntGJIfwOVqyF3LJzXcpK8Y+E8Ea2/JbuZSJ74JN83kK38DMfpyhwmnHLSRSuGdLuctB6yicA3pqNr\nhO+4KSnInvh6Mp1daHoy7o8NWgtwX7p/EWuXzmdaUYZBdVqbfBlHiC7RtMsZm1h0XKMwiuSTZCHn\ns/rvZLpGSJa8l8OIHa8PtJSZPP3Kfq6YeyqTBAgxJLeVaUYA2tSDCRe9uz9bdZFCxmdyPsOXrvvI\naE3F5HyGgpBdn2TXiOFK0NE1QsLY4HBHbcB51VmcYs7nMxv6O7bukEBcRAOMimgkqAfrEYC+NsVu\n0hEA97cyXaTZkO7kyfnRhnRSek2BbEPgnGc6ji0n5N5JRXK+DmSLaCAdM2C3l3rlqDDGUMz5LaGY\njGcwAvI+oYV81msZmzH115UTl2a+TmLHaUgvhDYRpGUG7PZvrctILuKE+kO2vENnZgmhisjCuv/v\nNRaefxqTC1nefq/Cth+/xa2Xz0n70pT3QXK+DmQvymrjdAIgOf4MskMVPTmPay+a2eb20ZPTCLiS\nHpIX5bRsnNyfibuI5Ekd6qGKlR8/p82mSkSoIub2AYy6faxdOt95w1zJSLbfaiJVRJOW2lrfzTGk\nFzr2NExk8w0pcdNUtkeAtFiynF8ypWrQ2X6rKuM9J5lC1ufldwb5y5vrNWh/efN8Xn5nkIKqByeO\nnnHUdRJadwBUwoihSsBdm3cz756t3LV5N0OVgEoYpX1px410FZpUiuNsNo7RcFWZQKq1kF877UP8\n3jd3MPfurfzeN3fwa6d9iGrCnpi6aMWIt+7Yc98i7v3keWx8di8jAoxJAaKIjo4YkftrlmjXCMlI\nd6GRTC2yHc2Oa1Gykl3dzsTozWd46Lsv8+A//nT0tYxn+PRV56Z4Vd2jmB8nZ5d3f2KXnPCWjGfG\nyYsIum1RZCnVQnHPZVoheT1pxZAeYpK+q20mvD3T+FvAxNAkiixDlYDINv5OeDc7UeR8j0kNF5pm\ngeqkfGZCilQngmYZzfJ125l791aWr9vOgeGqiPuXlgZAxpPRJaSHmIq5uu1K6/j6xKgjpSJ54qtG\nEeGYcYSRpSohZk29jGbDM6+3pBw2PPO6iF5oaTnsaOfiMUg9yjcJw4hS7XBr82LWxxe0q5V47yR3\nvx0qByxf32FsSxckWuszUUjuFg5dn0+0c7HSStNxesX6utpnxfodDJRqInbskk8jkusHJedZQXa3\ncADf9+r+rKbu2zoRG2BdtGJInvhAdtt20WMTnGuVnmfV+sHuo4tWDMkTHwjfsUseW3acXKSAXKv0\nPGvThWbb7Vfyyhc/wbbbr2Tlx88RseGAdARCutzHkDzxQf0N9OdL+rjs7JNbGu5JsXGS6qYNh1tA\nNPu8SVHX1UsV8mJLFXoyHosvmcWqjYdtquqdmd2/f2kZjLv/m+si0m2cCr7H/DOncdtjO5l791Zu\ne2wn88+cRkHABNiT8cZp2+7+2JotID62+nuc/cff5mOrv8fvP7ZTTARAcqnCSBB1LMAdCdxXR6YV\nmXJ/C9pFijmfB66/oE3pI+WkNRIcdvxoGuZufHYvt1x+FpMdn9xHgqjj2G69Yg6THF+UizmfGVPy\nbLv9ytGxPfy9l8U8l1JVnyA7eqOtSU4ARmoRT+3a1zLxPbVrX33iy7s98UH9IevUvkPKG0iqm0m5\nFvJfrzkPa8EYmDElz3+95jzKtZBizu23cBRZBss1DpZqnDGtyP7BCicVs2I6hpcq43RWSLh9x0SQ\nVmsS92fiLlLM+iy59Ezu3fIC8+7Zyr1bXmDJpWeKSHiDbPmtZIWdB1SCqCWsWwkiEW/eci1kcIyJ\n82AloCwk9JnxYPEls1rmlMWXzMLxwAZwuDVJPCQ/Ea1JtLh4DJJDFZG1zL17K0FM4ZPxDC/dvwjP\nuD1GyV2nB8v12rqxBbj1XmHZFK/s+JFeXCx5fJG1fO7xfm772DktYesHb+w71vnkiL7I7d+aclQ0\nhSZjj/PDlcD5yU+yYa7kWh/pxcWSx1eqhsw5ubfltTkn9yau2BVwSO0e0ouLs57pqLDLCpjYJSO5\nAFe6YlfyvWvK+ceGPpNW7OqiFUN6cXEu67P1x2/x8E0X89L9i3j4povZ+uO3yAnI2TUT+vsHK1gL\n+wcrDJZlWFQ123e05Q4E7DV8Y/jKpy5sGdtXPnUhvuPh6iaSi6fTkvO7H1/oIpLlqVA/zv+iVOPt\n9ypMLmR5+70KvyjVRBTgloPDCf14X6ZsxnNeYVfI+kxutO9oFhdPzmcSb2s+ERRyPn/2d7tbFLt/\n9p1/5cEb+9K+tK4guXhapOTdGDMV+CvgfMACtwJ7gMeB2cBrwKestQeNMQZYA3wCKAG/Y63d2fg+\ny4B7Gt/2PmvtuiSuV7I8FerFxUs/OptDpRoA+Uz9YwnFxfGuzMBoV+ZHli5I+cqOH887bEZqDJw8\nOS9m4itVQ95+r8LCr31/9LXL5kwXsZFq0iyeBsSMCeRK3tcA37HW/jvgQuBF4I+Af7LWngv8U+Nj\ngEXAuY0/K4CHAYwx04A/AS4FLgH+xBhzUhIXK1meClANI4bGyIuHKgHV0P3qfMkJb5DrGiG9hx3I\nbeApTvJujJkCPAfMsbEfYozZA3zMWvuWMeY04HvW2nnGmL9s/HtD/POaf6y1v9d4veXzOnGsknfJ\n8lSQPT7JY5OO9B5vUksxImv55tOvcU3f6aNept/qf5ObL5udqOQ9ySdjDvAu8A1jzC5jzF8ZY3qB\nGdbatwAaf5/a+PzTgTdiX7+v8dp4r3cd6bt1yeOTnPCWjOQebyBb3FWuhVz14RktRe9XfXhG4oXh\nSS5aGeBi4GFr7UXAMIdDgZ3otMra93m99YuNWWGM2W6M2f7uu+8ey/WKlqcClMaRF5cEyIs9zzCt\nmGPt0vm8dP8i1i6dz7Si+7tZ6Uie1EG2uCueR27euy88+TxRwtmGJBetfcA+a+0zjY//lvoi9nYj\nLEjj73din39G7OtnAj9/n9dbsNautdYusNYuOOWUU47pgqXv1nuyPmvGjG/Nkj56BOQP6jv26pgd\nu5waO6lIntRBtr1YWpGbxBYta+2/AW8YY+Y1XroK+AmwBVjWeG0Z8K3Gv7cAS02d/wD8ohE+3Ab8\npjHmpIYA4zcbryVCs2/RnvsW8aXrPiKmbxHU6yp2vDbQUqe147UBGW0SqiErN/SP2bH3i5gcJCM9\nuiG5gWdaheFJZ6g/A/y1MSYHvArcQn2hfMIY87vAXuCGxud+m7rc/WXqkvdbAKy1A8aY/w78qPF5\n/81a27q8d4lm36K2ZP6yBSKkqj1Zj/N+dSq3PbazxeW9J+v+wiw5XyeZpgLtC08+31Jfl7QCbSLp\nyfo8fNPFo2KFjJCQdVqtnBKdia21/UCnQpmrOnyuBf5gnO/zKPBod6+uHel9i+Iu78Coy3vdeNXt\nWaI0jq9iqRIwyXFfRckUsj6rt+1pKS5evW2PmOLichByaKTWYVE2zhe9p9XKye3fWpcp10LuWDiv\n7QGT0LcIZBuvesZ03rELsQOSivTiYslF7/VWTrNYuaE/JudPPvTp9va6y6SlhpkoJCeFC7nDO/Y9\n9y3i3k+ex+pteygIOSVLRXpxsfSwdRoaAPe3Ml1E+gPWnCDGFjpKmCBK1ZCF581gxpT8aHffhefN\nELNjl4rkljIgux1QWhoAfTfHaJ5E2vIiQiY+yRNEwfeYP3tai8hkzZI+Eb6KINs1Qqo3H6QnVpgI\nRBrmuobkk0gTqRPESBCy8Zm9LUnhjc/s5ZbLz2Ky4+aRYRhxYLjKqo2HcwdrFvcxvTcnZuGSykg1\n4oWfH2pRDz79yn6m9Z7KJNfFT9VxDMYT3uQn5j2YJsfqPQj1ItVSLRR3EpFOGEW8ebDctqM9/aQC\nvuP66cFy3eZobBimrvp0O8QknTCMGKwEHCrVRtvKTC1mmZzPOL/hSGAzlbr3oJNIddOWTqkajspv\nm0KMp3btEyEykaz6lE5lnM4KFQGdFbQJpKIcB8Wcz7UXzRSZO5CczJdOFMHmHa21TJt37OPWy+ek\nfWnHTVp1rRoe/IAhNfwpOYRWrga8Vw7awjBTChkKAuoHJSM5bF2qBpSqAUPlcDT0OangU8xljrWu\n9YgmIn3iP0BEkWWwXONgI76+f7DCScUskwtZ5xeu3nym465PQggtl/GZlIe/vHk+kwoZhsoBGc+Q\ny7h/ipSOZBcaLJRrEXdt3t1S0F9MeI/o/ju6y0g9iUDd8WOwEV+PP2RZ36Po+ORero7jZlINnR8b\nwHA1aHMeKAhRtUp+z0nOR0Y2HbcPx5f67lLvMlph+brtzL17K8vXbefAcEVMe4v4Q9bi+CFgeJG1\n44zN/cHVe051cLAX0HNK+ntOsou9uNYkLiK9vUUxfzhx+soXP8G2269kxpS8CMeP4jg7WgmnrHjC\nu+W+CRCZSH/PNV3s4zZVUlzs01qQ3X9Hd5H4pN6ihhEwqUM9hPaHV/87Pv/Ec6Nhpq986kIRIbTm\nG6jd5T1kUsHtsUk2cpZunVbI+rz8zmBLPnLn3gGunHtq2pd23DSb5rYZ5qp68Og5VvVgqRIwUKq2\nTQ7TijnnJ3WAoXKN5R0Udo8sne98+45SNWBguMO96805P7EPlQOWr9/e4b4tcH5Bljw2kK/87HI+\nUouLj5ZwnLxIKGRhlxxCi/dlanF5FyBWkHwayXiwZnFrZ981i/tw3HlrlFpk2fjs3pbncuOze6kJ\nydlZa2kefOL/ThL3Z6suIlnpA7JDaJL7Mkk2cg5ik/qoZ+Sze7n18rPSvrSuILnoPS1PTCH7me4g\nud8UyE4KS+7LJHps+Qyv7h9uee3V/cMiTv/QWqfVjN7cuel5EXNKqRZ2tHFKWtWqOa0Ydflttc3l\nfXpvTkTdyNji4jcGSmKKi0F2vY/UsUnPI0fWMvfurQSxcGDGM7x0/yLnu2onMDbNaR0tnmc4qSfL\n2qXzeen+RaxdOp+TemRM6FAf3+RClpMn1xslnjw5L2bBAjU7dhHpeeSmb2Scpm+k66Q1Nl20YoRh\nxECpyor1O5h791ZWrN/BQKlKKMCRWXGXZgSgtQC3KqIAV3oeudkEMh7alZLTynqmo4gmm/BmUcaT\n0SVKtbBjUviWy89isuO9b0C296BkSrWQDc+83vJcbnjmdW69Yo7zQgzpDvbxljnNe/fUrn31OcVx\n78Fc1mfr9jdaGlx+q/9Nbr5sdqI/1+0nvstIVvoAlINxvAcznvO1TJLpyXodn8uerNuTHshuRw+y\n55ThSsB3fvw2f7LlJ6OvXTZnOtddPDPRDYcKMWJIbm8B8gs5pYoVJD+Xg+Ua3/jhz9pattdPIm6P\nDWCoEvCDl97hsrNPHj2NPP3Kfq6Ye6rzp+RKNWAkiNq6MvdkPPLammRiEB9fF1ykKln5Kfm5LGZ9\nFl8yq63WR4KcH6An4zH/zGnc9tjOlvH1CKiervcDa8/3J90nzP2nvotILuKEenHxyo+f07arFVFc\nXAtZuWFSpXHXAAAgAElEQVRXS5uElRt28ciyBc7fO8l5H9/3mN6bY+3S+fTmMwxXAopZP9Hi1Ikk\n3pIeGK1lemTZAiY5PsZqGDHUId2Q8z0yCS7Kbv/WukxPxuuohpGwK4J6bmTxJbO4d8sLzLtnK/du\neYHFl8wSkxvpeIoUkDvIjaPSyjl+gmzi+15dDGTqJRlSFiyQ/Vym1erI7S1olxkJIna8PtCihhmN\nPwt4I0ne9ZWqIX++pK8tdyDhlOx7HsWc3/JcZjzjfLv2JlJzkSA7epNWusHt31qX6cl6nPerU1vi\nz1JUWiB711fwO+cOCo4vxgAjQTi+EMPxKECzCeTY9hbTe/MiFq6mBdfYXKuEnF1aYWtVD8aQrNIC\n2eOTPDbJVkBD5YBHf/hqW5711svnOJ9nbSL1JBlGEQNDVYar4ah6sDfnM21S7lijAGrjdLRIVmkB\n+MZ0NMz1HZ/4QPa9k2wF1JPzWHLJLPKNE2M+U/+4JydnapJqL1apRdQiy12bdzPvnq3ctXk3tchS\nqSXrICTnyegCkicHgEJunJ5TAsKDku9dWnY5E0GlFlEJo5aJrxJGiU98E0kUWYYqAZFt/C3Afgvq\nvpGff+K5FiHG5594LnHfSPe3oV2kOTmMrRmRMDlA3VG7Y8+pSuB85+Jiti5UGFvoKCF3EESM03Nq\nTtqXdtzEFWjAqALtkaULUr6y7iA5Z5dWdEMXrRiSJweohym+emMfn3388Bvoqzf2Of/mATDGUGvs\n2OOTgxEQ+izmfR767ss8+I8/HX0t4xk+fdW5KV5Vd5Bc8A5Qqgas3NA/pn6wn0eWznd+o5iWMlLD\ngzGak8PCr32fs//42yz82vd56Lsvi3kDFbI+f7r1xZbw4J9ufVFES/p6cXFrQ7qVG5JvSDcRSA59\nSh4b1Jtcdl6U3T8vpFXXqotWDOlvoHhL+uai/PZ7FRFdVCXL+Ys5nwdvvLBlcnjwxgvFjE1q6w6o\nu9B07IZecf89NxJEo5Gp5iZ447N7GQmSzUeq5D1GpRrwi3LQltP6UCFzrAaQJxSS/fmGKgHL13Uw\nAxZg41SqBpSqAUPlw9LiSQWfYi7jvDu/dMm75M7MaXUudvu31mVq75PTyqd9cV3A8wzTe3M8smyB\nuJqRnozHmiV9rIolvNcskWHBFUXwN/+yl4XnnwZAJYjY8i9visi1eh5cN39m26QuxOwDgELW40vX\nfWR0w1EQYlaQVk5LT1oxJBdxSqdUDRiphgyWg9HJYXIhQ0/Od/40EkYRbx4st/VkOv2kgvNWTmEY\nMVILCSLbYlHVI8Q0N7KWzz3ez20fO2d0I/zw917mwRv7nJ9TxjaVfWOgdLxNZfWkdbSUxrElkSAJ\nl04UWT79N7s69Aqbn+JVdYdSNeTOTa2y8Ds3Pd9w+3B7Yq+EEcPVkNtjIfmvLa4rWosCFq3hccpM\nJDj0Q93pfaxiN2ncfyq6iGcMX/lUa8L7K5+60Pkd0QcBySotyW4fUWS5fWOr6vP2jf1iCnAlC03S\nUuy6/9R3kXym7qYdjz8Xc/6oxYwEpPqglSrjuLxL6BUmOAJQzGeYMSXPttuvbAmfSdhsQP2U/MLP\nD7V1jjip9xTnT8lpKXZlPBldohJGBFGrXDOI6jYzEkIVktWDWY+OLu8Sct6eMfz5b/e1qQclRADK\n1ZA7Fs5rE2KUq6GIhasn4zN/9pjnckkfPRkBJ63KOEKMhDeKKsSIMVQOWL6+g2x66QLnd+tQl4U/\n+oMO8uIr5jgvC5fs8h5GEf/2iwp3PPnc6MS3+oYL+ZUP5Z0XYki+byB7TilVAwaGO8j5e3PHKn5S\nIcbRUsz7XH3+jJaj/Lf63xTjiNGT9bj2opltKjQJ/cJ6xwkzScj7lKohdzz5XIsQ444nnxMhxJCc\nrwPZNlWF7GED7uZ7bvW2PTx4Y7JiDLef+C5TrYVc03c6h0o1rIVDpRrX9J1OVYAVELSq0JqJ0zs3\nPS/CEaNcDbnntz7c0uLint/6MGUBY5M8sZfGcaEpSXGhEeyIEVdGxh12knYQ0kUrRmTrIbR4m4R6\nS4G0r6w7xE8jr3zxE2y7/UpmTMmLmPwAyrXWFhdlIe0tJE98njeOYtfxHGsTz9Cxh52E4aWljNSc\nVgzJ8WeQbSkj+d5Jvm+RtXzz6de4pu/0lpD8zZfNFiE0KVUCSrUOFlzZjPP3LoEcuea0jhbJ8Weo\nN23bva9dfnv5uaekfWnHjeR7l896TM5nWu6babzuOuVayH+64DQOlWpMLmQ5VKrxny44jXItdN7J\nBOqNV5/c8QbX9J2OMTC1mB1dlF2nmPVZcumZbWrkpHvYuf9UdJHhcephpFSv92T9jrLwHgGtSSTf\nu0qt7hrx+ScOqwe/8qkLyfoexbzjC5c9HNaNnyKLbt+yUcrVkKs+PKPlPSdF0p+Wl6njT3x36cn4\nrFkypj+MkJoKgJFayKox7gOrNvYzIkBo4o/jZuILCDGl1dZ8Ioh3Lm6O7QtPPi8mjxxa23F8Eu4d\ngLWWZoop/u8kcXup7zIjQcjGZ8a4vD+zl1suP4vJAlwxJKvQCjmff9jxRlu5goQwjOT7JjmsC7Lv\nXRhGHBiutrVymt6bS9Ts2P2ZuIv05jMdOxdLeMBAdpPLeBhm7t1bue2xnVz14RkiJO+S1YOSn0mQ\nPb7SOJGbpL0Hj2jRMsasOpLXXGe4ErDy4+e0SMJXfvwcEQ8Y1ENoneS3UkJoUsMwnjeObFrAlrOY\n7RySTzqZP1EUs37HlvQSxpdWCc0RSd6NMTuttRePeW2XtfaixK7sODhWyXu5GvBeh87FUwoZCgKU\nTKJ7+wjuhSb5vgEEQcRIENKbzzBcCejJ+GQEhOObhGFEqXZ4fEUhvcISKMU4fsm7MWYJ8NvAWcaY\nLbH/mgwc6PxV7hJEjB53gdHj7iNLF6R8Zd1Bcm8fyerBUjXseN+S7hA7EUSRZbgacLBUo5jLcGCo\nWm8k6B1zI8ETDt/3mNxYpFx/FuNEsegGMBrdSLqH3S974v838BZwMvCV2OuDwPNJXVRaSE8KF3M+\nDy3uY7h6uNCxN+eL6O1TzPn8xU0XY6GllknC2HoyHg/fdDGHYh1ipxaz9Ag4jZSDkMGGC018t57N\neCLqtEBuO6C0eti971NvrX3dWvs9a+1l1tr/Ffuz01orI9ETQ7oPWqUWEVparI5CW3/ddWpBRCWI\nWoQYlSCiFrg/tkpYH1v8vlWCessc14micSTv7g8NONwOaPm67cy9eyvL123nwHBVRJPLtObLIxVi\nXGeM+akx5hfGmPeMMYPGmPcSvbIU8MYRKkjIG0BdrPDZx1vVPp99vF+EWKEW2Y5KppqAyUFyd1/p\n0Y16d99dY7r77kpcYTcRFHMZHhojonloSV/iJ+Qj/e5/Bvxna+2LSV5M2hRyPqv/buKt9icKyTUj\nkseWVhhmIkirkeBEkVZ334nAWkvW91o6vWd9r1FgnNxG/0ifirelL1hQfwN1THgLeQNJFitIHpvk\nib2Y83loSR8rN/TH/Ov6REzqIPvelWohtz22s3MDzwTVkUcqeV8D/ArwFFBpvm6t3ZzYlR0HKnnv\nTBhFvHmw3NYE8vSTCs53wJV87ySPDeQKFSCR7r4nDAmUmRzRFx3povWNDi9ba+2tR3tVE8Gxtyap\n8egPf9ZutX/5WUxyfLcO9dbm3+gwvlsuP8v900g1IAgjIntYPegZyPjuq9Ak3zfpSK6xS+C57Gpr\nEg9YZa09BGCMOYlWCbwIig0bpwf/8aejr2U8w6evOjfFq+oePVmfxZfOYlUsFLNmiQyX93zGa1MK\nWstoJ2OX6RX+XEotvgXZNXY5z7D4klltEYBcwqfkI/2tXdBcsACstQeNMSekG8bxUBonL1KqBCJO\nWtUgwjemJXHqG0M1iMg4PklUahGDlaAtDCOhfUepYS82dkcr4blMy3R1oihmfR5actGE95yaCGrv\nY8aQT/DnHml48DngY9bag42PpwH/y1r7kQSv7Zg51vBgqRpwqFRr61s0tZh1PsQE9fDn8vU7OnT3\nne/85Ce5c7HknNZgucaKDs/k2qXzxYQ+pdpUpZXTOtIn/ivA/zbG/C1ggU8B9x/LVZ3IFLI+f/ad\n3S2S9z/7zr+KkbxLlk5LrveRbC8WN12N53wklCpAfcEaamyGmzZVU4tZJpFxfuFKSxl5RN/ZWrve\nGLMd+Dj11fA6a+1PEruqlJAcf4b6+Do+ZALGJzmEJnlBLldD/vDqf9cW3ZDQ2RegGkYMdbCpyvme\n84tWxoM1i/vaIgBJD+uIv7219ifW2v/bWvvnEhcsOBx/bq3wlhF/Bij4Xsc2CQUBuYOMZ1h86Szu\n3fIC8+7Zyr1bXmDxpbPICJBOS+7JFI3TlTkS4NICsjszBxFsfLbeNHfPfYu495PnsfHZvSTtnHZE\nOS3XONacFsiuGRks1/jhT9/lsrNPHpWFP/3Kfi4/9xTn8weS83WS6+skt5QB2eNLK6eV+BNvjPGN\nMbuMMX/f+PgsY8wzDS/Dx40xucbr+cbHLzf+f3bse9zVeH2PMWZhktfreYZJ+QyeafwtZMGCuvvA\neb86tcVU9rxfnSrCfUByvm6kFvHUrn0tO9qndu1jRIDRseRTJMg24U7r3k3ENm0VELeAegD4qrX2\nXOAg8LuN138XOGitPQf4auPzMMb8GrAYOA+4Gvgfxhj3Z9kUKFVD7tzUGqq4c9PzlLQl/QlNMeuz\n5NIzW0KfSy49U0TYupjzeeD6VpPqB66/QMRGCuom3F+9sTUk/1UBhcWQ3r1LNDxojJkJrKOuNPwc\n8J+Bd4FfsdYGxpjLgHuttQuNMdsa/37aGJMB/g04BfgjAGvtlxrfc/Tzxvu5xxMelIzkUEWpElCq\nBQyVD/cKm1TwKWYzIk5bUgtwpbt9hFHEwFC1rYfdtEk550O7J7ojxrHyNeAPqXc6BpgOHIr14toH\nnN749+nAGwCNBe0Xjc8/HfiX2PeMf41yFEg278yYetI7rtJas6SPjNtrMVDPsw6Uqm2mstN7886H\nr3sy47i0ZGSctErVkO2vD3DZ2SdjDEwtZmN5ZLcXrWLO59qLZrblWpM+aSX2WzPG/BbwjrV2R/zl\nDp9qf8n/vd/XxH/eCmPMdmPM9nffffeor/eDgGcYp19Y2ld2/FQiy6oNY/ppbeinIkCmVaqGbHim\nVaW14Zm9IsK65TBi45ixbXxmL2UBDS6hvihfdvbJHCrVsBYOlWpcdvbJIhblkWrYOdea8HOZ5Pb6\n14FPGmM+ARSAKdRPXlONMZnGaWsm8PPG5+8DzgD2NcKDHwIGYq83iX/NKNbatcBaqIcHExmR4+Sz\nHvkx/W/yvkc+6/aOD2T30+rJeSy5ZBbDjckgn6l/3JNz/74Vc75oX8VqNE6dVsYjMyGSguTwPMN1\n82e2WaclffpP7Ldmrb3LWjvTWjubupDiu9ba/wP4Z+C/ND5tGfCtxr+3ND6m8f/ftfWE2xZgcUNd\neBZwLvBsUtcdRZahSkBkG38L2Kk3GalFbH99gKnF7GioYvvrA6pCO8Gp1CIqYcRdm3cz756t3LV5\nN5UwoqL37YQnisap03L/1lHI+qzetqflpLV62x4KCQuE0tiG3glsNMbcB+wCvt54/evAN40xL1M/\nYS0GsNa+YIx5AvgJEAB/YK1N5PwZRZYDw9U2c8vpvTnncwcAPRmP+bOncdtjO8fkD9ze8UHdwb5T\ndb4EB/t4gSowOvFJsHEq5nweWtzXJlSQoh6U7GaSloOQFhfHGKoELF/XwXR12QLnbY6gbir76A9f\n7dAvbI7zQoyhSsAPXnqnrXD6irmnOn/vRKs+qwHvjQR89vHDm42v3tjHlJ6MmlSf4CSwyT8h1INO\nUcz5Hc07pez6ROdGsj4fPftkDpZqTC5kOVSq8dGzTxZRyyS5ZU4UWT77eKsZ8Gcf7+eRpfNTvrLu\n4BnDl2+4oD3v4/hmA+o5rem9OR5ZtmBCHYR00YpRrobcsXBe2wMmxbwznhuJj69Si5zvOQV1c9L4\n2B5aIsOd3zOGr3zqwjZTWQkTn2QnE4BCzmf13+1p6RyxetseMZ0jmg5CwIRFNNyfqbpIZO045pYy\nQqiSzTtL1ZCVYyTvKzf0i5CF5zMeUwoZHr7pYl66fxEP33QxUwoZEV2ZJdscQV1o0sz7nP3H32bh\n177P2+9VxAhN0sD9p76LSN/1SU4KSx6bMYaRWtjiGTlSCzECTlrN8Fl77aD7YwPwxxmfL2R8aaCL\nVgzp8lvJ/nyix1Yb5xRZc39shdw4smkheWTp40sDGUeILuGPkzSVsisq5nweWtLXZgckQWjieXRO\neAvYlhVz45wiBdy3ePisyWVzpjNcCUR4D0pvLJtGKyeVvMeIrOVzj/dz28fOaVEPPijElTmKLKVq\nQBDZUVl4xjMUc+63YIkiy2C5xsFSbbTe56RilsmFrPNjk1yKIblXGMh/z6nkPWWk7/rKQcihkVpH\n2xUJNTG+Z1rcPnzHJ4Um9Y7aHU7IEuT8Mf+65kbxqV37Gk7hUhatsK3ovZBxv7lsqRay4ZnXW+7d\nhmde59Yr5mhx8dFyrCct6bu+oXLA8vUdduxLFzhfXFyqBgwMV9sW5Gm9OecXZMmnyDCK+LdfVLjj\nycNy/tU3XMivfCgv4j03WK6xokNx8dql853fCCcwX+pJ62iRvuuTrLCLe7yBLKujUjXk9x/bKXKz\nMVKL2LTjjZb33KYdbzR26+6/5yQbOcebygKjTWXrC3Jy9879p6KLFHM+Sy6ZNVr/0nSMkJDwBtnq\nSMkLsuixZX2WXDprTFfmWSJCnyD7PZfWgqyLVoxKELWFWzzPUAkEWDJTX5RX33BhS83I6hsuFLEo\nSy5SlSznB8g12uXsuW8RX7ruI+QEdGRuklZL+omgVB3nuUy4oF9zWjFKlYBDI7U2u5ypPVkRBcZD\nlYBHf9DBMDfhxOlEIDmnJXlskpWRUM8j/+CnHYyczz3V+dBuWupBXbRiSHZkBtmtVySXK0gWYkh2\nsAcoVwPeqwSsiik/1yzpY0o+Q8HxDQd0vU5LhRhHi3QbJ88znNSTZe3S+fTmMwxXAnoESG9BdhGn\n5xkmF7L4vocxcPLk/IQUcU4EzRBTm4O9gPsGEESWVRtaXexXbRDkYq+GuekiOS8CEIYRAyNVVqzf\nwdy7t7Ji/Q4GRqqEofs5u3ot00UtuYOHllwkJqHfnBw80/hbwIIF8u+b9I1wGp3eNTwYo1QJGCh1\nyB0UcyIeMsk1I5COpcxEoWNzE8m1kQmErY/oi/SkFUO6uaXkmhGQexpp5iKXr9vO3Lu3snzddg4M\nVydkVzsRSL1vAJ5hHBf7tK/s+CkHIYOVgLs272bePVu5a/NuBisB5SBZ9aCM2apLSLdxKlVCVn78\nnDb1YKkSOr/rk0zd5X1XS15k5YZdYhR2kk9a+axHviHpb55G8r5HPuv+eSGtgn73f3NdRHJNBUDG\ng8WXtBZyLr5kFgJ6CYpGsst7M8S0f7CCtbB/sMJguSbmFDlSjdjw7N7RWs9KUP94pCogj5xS0btO\nVzHiNk7N8OBTu/aJ6H4LDSXTxta+TKs29rfIjZUTj7SKOCeCchAyXA1bQkzD1TDxENNE4Rm4bv7M\nlo3idfNniggPplX0rkKMGNLNO6XXxEhFcn2d9NrIMIwYrAQciokVphazTM5n8B13/gjDiAPD1TYH\n++m9uWMdm9ZpHS2VWsSkgs/DN108Wr1uTP31ogDzTs1puYnnGab35nhk2QJxeR/pknBjDDnfY1pv\nDmNgWm+OjGcwAjaJI0HExmf3tpgdb3x2b91hJ8EFWcaT0UUGy0FHybsEmjmtsTsjKTktyQn9NIo4\nJ4JmiKmtuFjIRqochJRqAUPlkN58hoHhKpMKPhict+Aq5nxe3T/c8tqr+4cTz7UKma66Q2QPq2Ga\nOZ8vPPk8UlI+QcQ4Oa20r+z4kS4Ll4pkSTgAFqqBbcnZVQMLAh7Lci3kjoXzWvJ1dyycR7mWbE5L\nF60YkltAgOzxxWXhzQV55YZdlBJ+AynHRz7jMSmfaXF5n5TPjLYHcp3IWj7/xHMtz+Xnn3iOSICW\nIC55b9nkJ7wJlvFkdAnpNk6SVWiSZeGSMcaQ8QxTi1mMganFrJicD8jO2aW1CXb/N9dFirkMDy3p\nY2XMkfmhJX3Ox56bFHyPNYv72nJaBcdVTCDfeFUqpVrYWT0opHBasvgprXykSt7HEIYRpVo46oJe\nzPrOS1ObDJZrfOOHP2t7A91y+VnOO35IloVLRnJLGWi0JikHbRvFKQX3W5OUqnUpf1v/wWL2WDf6\n2k/raJE+8Umv05KsHpRKAhPfCYXkOrQwihgYqjJcDUdr0HpzPtMm5Y61rlUNc48W6cn84XFydsNC\ncnaSjVelEkXjCBWEqD4l57RK1ZCVG/v52OrvcfYff5uPrf4eKzf2J54j10UrhvRkfjHrs2ZxX4u8\neM3iPjG9ixT3KOYzzJiSZ9vtV/LKFz/BttuvZMaUvIhJHdKzOpoI0uoaIePJ6BLSk/m+7zG9N9fS\nuVhSzk5xj3K1XusztqC/XA1FLFw92c7ipx4BLu9pzZea04qRQFMzZQLRnJZ7SG9MOlQJePQHr7aJ\nn269Yo7zG+EENADqPXgsVMOIuzbvbpG8Kyc+9TdQpa1cYXpvXheuExjpjUmLOZ+HvvsyD/7jT0df\ny3iGT191bopX1R3S8sR0/4zaRUrVkJUb+scIMZJPLCrHj947N5EuDpKc04J0xE+6aMWQbHMkHb13\nbiK98arnjeOtqDPvMaO/uhjSd0VQD6MNVQIi2/hbiLT4g3DvJDJSjTo2XpXQ2RegkPVZvW1Py/hW\nb9tDQYhiN435REbguEs0HafHKpmkpEQkF083d7Rt907ItkyqyMTz6p19pd63UjXk7fcqLPza90df\nu2zOdBGK5LTmE1UPxihVA0rVeu+bpnpwUsGnmMvIqM6vBCxft12kz5tk5aeOzV0kjy+B+UTVg0dL\nIeNTCyLgcEgp63kUMjKO8pKLpz3PMLmQxfc9jIGTJ+fFnEbKQchgJWhRtX75hgvIZjznN1OS71sT\nqYrktOYTt5/4LjOqhPEMxsD0STlRbyDJjtMgt7tvvG8RMNq36JGlC1K+MuWXUbeG62+5dys39IuI\nbpSq48wnCYc+3f6tdZkosgyUaiJzPgAZDxZfMqutOl9Ivz2xDv2SlZGS86wgO7pR8L2O80nSrY7c\nf0d3kVItZMMzr7cofTY887oYw9wgglUbW2uZVm3sJxAg1ArDiAPDVVas38Hcu7eyYv0ODgxXCUP3\nBydZGSndpFpy49WRIOw4n4wEapg7YfRkPa69aCb3bnmBefds5d4tL3DtRTNF+ISB7B17qdb5DSRh\n8ivmfB5a0mp0XG9O6v59K+b8zoa5AsYGdZPqh5ZcNObeXSTCpFoNc08AStWQOze15g7u3PR8wwfN\n/YUrrU6jE4F0O6Cc7/Gl6z4yqkDLCQh7ApRr4xjm1kLnRSaQntXRRNB0Mxk7nwxXgkR9I2U8+V1C\n+sQneccu2Q6oVA35/cd2tvQt+v3HdooIMcVFJs0T8heefJ7I/ajuKFL7vKXV6kjGbNwlpLcmqe/6\n8iJ3fcWsz8M3XcyhWD3M1GJWRBhGclhX8tikk1arIz1pxZAcf24idddnjKHWqIeZd89W7tq8m1oY\nYYz74xMtxBAsVPgg4PtevVDaHK63Sxp1xBiDVLsc6Uh2+yhXA94rB23S4imFDAXH8z7SJe/KUaGO\nGMeC1AJV6Uiuhwki2PjsXu795HmjRZwbn93LrZfPSfvSjhvJQgUlGXRWVkQgOR9ZzMttJKi4TRBE\njASHC/p7Mj6ZhN0KNKc1BqmtO6QjOR8pOe/TDA8uX7eduXdvZfm67RwYrur7zgGCIGKg1FrQP1Cq\nEiTsVqA5rRhRZClVA4LIMqUny3sjNTKeoZiTI1iQnLOTauNUn9grrNzQ32K6Or037/y9G6oE/OCl\nd7js7JNH33NPv7KfK+ae6vwJWTqD5Ror1u9oyyPX61qPqU5Lc1pHSzUIKVXDDt58xvmEN8hOekv3\njZRaXFzIeMw/cxq3Pbaz1b9OiiGmYNKqa9UnI0Ytsh2tgGpCQhWSfd5Ej01wcfHIOPZbIwLuWxOp\nKYe0Cvp10YrxQXDEkKqwEz22/Dj+fAIKcKW/5yTn7HrGccToSTiPrItWDMlWQCB7fJLFCuVq3Z8v\nbuR8x8J5lAWMTfIzCbIjAOVaxI7XB3j4pot56f5FPHzTxex4fYByLVkhhi5aMbKeYc0Yb741S/rI\nCsiJQP00svqGC1vGt/qGC2WcRgSrB0NrO/rzhQJEVGn5100UoiMAOZ8Fs+v5yLl3b+W2x3ayYPa0\nxMem6sEYQRAxVA3a/Osm5TKJ1x5MBKVqQKkaMFQOR8c3qeBTzGVEOGpLVUZG1jL37q0EsZBSxjO8\ndP8iPAE2VVJVnyDbqQW6fu9UPXi0lIOI2x7b2f6ALV3AJAGLVhTBZ/6mv+P4JCDVzSStFhAThe97\nTG5MdBLGE6cZARirapVwkqwrdqsTXorh/kzcRaQ7Tksfn1SVVjHn88D1F7SE0B64/gIRISbpeJ5h\nWjHL2qXzeen+RaxdOp9pxayICECpGrJyQ/+YfF1/4nlkXbRiSHbTBtliBckqrZFaxFO79nHvJ89j\nz32LuPeT5/HUrn2MJJzwVo6f5kbqwFAVa+HAUFXMhiqtTbAuWjE8D758Q+uO9ss3XIAn5LckWawg\nWaVVzPos++hs8o0QdT7jseyjs0XcN+mUayGDlaClZc5gJaAs4LlMa5OvQowYUWQZLNc4GBNinFTM\n1vvFCDjOg4oVXCQMIw6UqqyK5Q7WLOljejEnRrAglaFywPL1HYQYSxcwqeB23jWBljlH9EbVJz6G\n59UbmZ08OY8xcPLkvKgFC+Q2gZQc+izVQlaNyR2s2tAv4hQpHcl55HjLnGbYeuOze0nYL1fVg2OR\nqkkR5SEAABWtSURBVECTTk/GY83ivrZdX48A1ecHwTVC4ukfZCs/02qZ4/47WjkqpCrsRoKo465v\nJOlt3wQgWSAkWUADjeLpDoYFEvKR6j2oJE6zxUXrBFERMUEUcz6v7h9uee3V/cMiZOGeGUcgJOAw\nIllAA/UatOnFXIvkXUouMq1SjMSEGMaYM4D1wK8AEbDWWrvGGDMNeByYDbwGfMpae9AYY4A1wCeA\nEvA71tqdje+1DLin8a3vs9aue7+ffaxCDOkMlQMe/eGrLDz/tNG27dt+/Ba3Xj7H+aSwZLePUiWg\nVOswtmyGouMhQskCGukMlmt844c/a5tPbrn8LGf7aQXA5621O40xk4Edxph/AH4H+Cdr7Z8aY/4I\n+CPgTmARcG7jz6XAw8CljUXuT4AFgG18ny3W2oMJXrtIenIe1140kzs3PT+a93ng+gvoybm/68PW\nDTzv2rx7dGxfvuECim6nDYD6SauQ8ckUPYyBqcUsGc/IOGk1BDRjcz6laqg55ROcYs7vOJ8kfdJK\nbLay1r7VPClZaweBF4HTgWuA5klpHXBt49/XAOttnX8BphpjTgMWAv9grR1oLFT/AFyd1HVLzflA\nfYK4c1Or8eqdm54XobCLLB1NZSXcvqzvUaqFLcakpVpIVkKISXDtYBOpc0paRe8TspUxxswGLgKe\nAWZYa9+C+sJmjDm18WmnA2/Evmxf47XxXu86kjv7Ql2F1uzL1DzOP/y9l0Wo0CRLi0eCaFTyDoxK\n3h9ZtoBJji9cnmeY3pvjkWULRKoHm3nkifbnmwh6Mh6LL5k14YrdxJ94Y8wkYBNwu7X2vff71A6v\n2fd5fezPWWGM2W6M2f7uu+8e07VKTwprXyY3kdzeQjpp+fNNBGkpdhNdtIwxWeoL1l9bazc3Xn67\nEfaj8fc7jdf3AWfEvnwm8PP3eb0Fa+1aa+0Ca+2CU0455ZiuV/rkEI3TlykS4IoiuVeYSt7dRXIE\noJir12kt/Nr3OfuPv83Cr32fh777srs5rYYa8OvAi9baB2P/tQVY1vj3MuBbsdeXmjr/AfhFI4y4\nDfhNY8xJxpiTgN9svNZ1JLsqABTHKVJ1XYEG9fj6ph1vtOz6Nu14Q4SpbMajY6NEAXXTlGohG555\nveW+bXjmdTHRDckbjrTmyyQf+18HbgY+bozpb/z5BPCnwG8YY34K/EbjY4BvA68CLwOPAP8XgLV2\nAPjvwI8af/5b47WuIz0pXBonhFaSEEITbCqbll3ORNCT9VhyyayW+7bkkln0ZAWsyMg24U5rvlTD\n3DFI7qJaqgQMlKp84cnnW2Th04o5509bkhPekbV88+nXuKbvdKb0ZHlvpMa3+t/k5stmO1/LJPmZ\nBPkm3F224DqiL9RFK0YUWUrVgCCyo5NDxjMUczKMZSNr+dzj/dz2sXNa1IMP3tjn/OQnuXA6ATft\nEwbJLuhNJHsrdpnUi4udoxqElKph2+SQ8YzzkwPUY9Bvv1dh4de+P/raZXOmiyjklFw4XYssqzaO\nkbxv7Gft0vkUUr6240WyUKGJmnB3F/ff0V0kPjmMtoDY2E9NipJJcM5OcuG0ZJd3yaUKTaQWF0M6\nY3P/qe8ikicHqO/4phWzrF06vyVnJyFUIfneiW5v0ShVuOPJ50ZPyFJKFUC2YUFaY9OTVgzpu74o\nsgyUaqxYv4O5d29lxfodDJRqInZ+kqXFxazfUfIu4YQ8Uot4Z3CEv7y57oL+lzfP553BERGlCiDb\nsCCtsbm/De0iPRl/nEaC7k8O0PqQAaMP2SPLFjgfay/mfB5a0temHpSwY/d9j+m9ubYTsgRVa8H3\nOH1qkd/75o6W91xBwNig/lx2sk6T8FymZcbg9kzVZcphxI7XB3j4potH1YNPv7KfK+aeyiQBlZyS\nHT/qHnZ5sR52xhhMQ+EZ/7frjAThuCKTyQLec03rtLGS/nI1dF7Sn5ZDv9u/tS5TzPl8ZkN/x94+\nEpDeBkKqSktyXkRyLhJardOAUeu0R5bOT/nKjp+ejDdOZMpxw1yXkJwXAdnqQZCr0pJsdSQ9jyza\nOi0lw1wtLo4huYizidRCR8mOGGEU8ebBclsN2uknFfAd9wMKgoiBUrXtPTetmCMjIDwouXg6ga7T\n6ohxtEh2VZCO5MkhgbbmJwxDlYB33hvhlMmFUZHJu4NlTp3SIyLEK3kzNVQJWL6uw3vu2IVd6ohx\ntBTzPq/uH2557dX9w6Kq86Ui2VkhrbbmE0Eh4zEpn2XF+jHqQQGnrCY53+NL131k1HswJ0UZ2Ug3\njM21qmHuMXCsJy3p5p0gNzw4VK6xfP2ODiet+Uxy/DQyWK7X1o0d29ql850/aUk+RYLsCACkY5jr\n/m+ti0SWcZQ+C1K+su4gWYXmGcOXb7igbcPhuhEwyFbYST5FQj0CcPX5M1rKaL7V/6aICEBauP/U\ndxHJISZoVaE1d7UbnnmdW6+Y43z+oJDz+acdb7dNDjdfNjvtSztumqrWtlKFSuj8bj3uGQmMekbW\nT5Huh9GqtZBF55/GbY/tbAl/Vmuh8+IutXE6AZDeubgnW3dCv3fLC8y7Zyv3bnmBay+aKaLhXrkW\nctWHZ3DbYzuZe/dWbntsJ1d9eAZlAbJwyY0EJZ8iQbYJd1o2TgIe++4hvY5JshN6FB0O7TbH9oUn\nnycSYGFXyPhMzmf40nUfYc99i/jSdR9hcj5DQYC9mPTaSMmLsto4nQDUrYByYq2ARL+BBId2Pc8w\nuZDF9z2MgZMn58U8l81TZFsuUsh2WrJDv9o4nSBItQIC4bkRwWMDuc9lIeuzetueljzr6m17ePDG\nvrQvrSv0ZMcx4RYQvSlmff7ipos5WKqNyvlPKmYTj0zJefqVX4pn4M9/u4+hcjj6kE0q+AjYsIvf\nsUtFcjdtgHLwPibcAuq1qmHEXZt3txROJ437vzXliPFNXdZ/1+bdzLtnK3dt3k1k66+7TnzH3vRB\nW71tDwUBO1rJSM8jF7M+C2ZPbxEILZg9XcT46kKM/jFCjH7tp6V0j2pkWbVhTBuIDfU2EPmUr+14\nkb5jl4r0PLLk8aUlxNCT1gcIyUKMZpuEsd19k26ToBw/zXydZxp/C5jQ40gdX1oO/fqOHoPU9hYg\nuw1EWm0SFOWDSjHn88D1rfWDE+Fmot6DMSTbHAGEYcSB4fY2ENN7c863bk+gTYKiKO9DAr6R2prk\naEnAav+EIwwjSrVwtA1EMes7v2BB/d49+oMObWUEWFSBXKPjDwJS710Cfd7UMPdoSSuxOJH4vsfk\nxiLlenFjnJ6Mx+JLZk146++JQHoEQDKS791ILeKpXftaauye2rWvsVFM7n3n/ju6i0j3HgS5ObuR\nIOro8SYhp5WWx5ty/Ei+d8Wsz62Xn8WMKXmMgRlT8tx6+VlaXDyRpFXhPVFI3vUVcz4zpuTZdvuV\no7u+h7/3sohT8gchAiAVyffOWkupGo7j9qEu7xNGs8K7WXxbDd3fqTeRvOsr10LuWDivxcH+joXz\nRLi8fxAiAFKRfO9KtbBjdENd3ieQer+pVtn0hmf2ipjUQfauT7LLu3TXCMlIvndp1X1qeDBGs9/U\nWDWMhH5TkJ4r80RQzI8THhTi8i7VVUE6ku/dcCVg5cfPaVPsJu1gr5L3GIPlGivW72iTvNe7qLqv\ntJNcp1WqBgwMV9sMc6f15ig63iFWUU5EgiBioNQ+n0wr5sgcm2r3iFZyt2eqLiPZ5ghku0ZIDg8q\nyonISNA5pzUSaE5rwpBscwT1nNar+4dbXnt1/7CInJbkJpCKciKS1iZfF60YaXlpTRSqsFMUpVuo\nYe4JQLzCuxk+e2rXPkZqMmJMkkNoklVainIikvVMx84K2YRFJirEiCG5+Bbkm8pK9XhTlBORUiWg\nFkVYy2hXZmMg63kUjy1EqN6DR4vnGaYVs6xdOr/FUFbKxCdZ8g6H+xYBIsajKCcyhaxPrRxxqFRj\nciHLoVKNk4rZxLuFa3gwRhRZBkpVVqzfwdy7t7Ji/Q4GSlUx/nwaQlMUpVs0N4nTJ+UwBqZPyk1I\nk0sND8YYKgcsX9+hNcnSBUwqyNi5awhNUZRukEA6Reu0jpa4q8IrX/wE226/khlT8qJk01JbfyuK\nMrGk5WUq4/jQJcrVuiR8rKtCuRoea2JRURRFJGl5mepJK0ZobUdJeCgwhKq4hdQ+aIq7pFUbqYtW\nDOk2TtKROrE3cwfL121n7t1bWb5uOweG5QiEFDdJS9ils3EM6ZJwyUiusYvnDoDR3MEjyxboc6mk\nRloO9nrSiqGScHeR3OBSch80kHtCVpJBt2kxpBcXS0byxC45AiD5hCydtO6dnrRi1IuLa2OKi2u6\n83MAyYa5kiMAkk/I0knr3umiFUPfQO4ieWKP5w5eun8RjyxbIOYkIvmELJ207p3bsYUuo28gd5Hc\n1hzk+ipKDn1KJ617pyetGJJDTB8EJLt9SBUrSD4hSyete6fegzE0KayciEh/LtUP0126fO+O6At1\n0RqDvoGUE42hSsCjP3iVheefxjmnTuLld4bY9uO3uPWKORpCUySh/bSOBam5A8VderIe1140kzs3\nHfbEfOD6C+jJyoju60ZRORpkPPWKIphSNeTOTa2emHduel5ErlUtqpSjRRctRTnBkeyJqWUmytGi\ni5ainOBIVrVqmYlytOiipSgnOJJl4ZIXZCUZVD2oKA4gVawgXc6vHBUqeVcU5cRH6oKsHDUqeVcU\n5cRHy0yUo0FzWoqiKIoz6KKlKIqiOIMuWoqiKIoz6KKlKIqiOIMuWoqiKIoz6KKlKIqiOIMuWoqi\nKIoz6KKlKIqiOIMzi5Yx5mpjzB5jzMvGmD9K+3pcRWrbdkVRPhg4UX5ujPGB/wf4DWAf8CNjzBZr\n7U/SvTK3UJ83RVFcx5WT1iXAy9baV621VWAjcE3K1+Qc2rtIURTXcWXROh14I/bxvsZrylGgvYsU\nRXEdVxatTrGrlmSMMWaFMWa7MWb7u+++O0GX5Rbau0hRFNdxZdHaB5wR+3gm8PP4J1hr11prF1hr\nF5xyyikTenGuILmZoKIoHwycEGIAPwLONcacBbwJLAZ+O91Lcg/PM0zvzfHIsgXau0hRFCdxYtGy\n1gbGmE8D2wAfeNRa+0LKl+Uk2rtIURSXcWbWstZ+G/h22tehKIqipIcrOS1FURRF0UVLURRFcQdd\ntBRFURRn0EVLURRFcQZdtBRFURRn0EVLURRFcQZdtBRFURRn0EVLURRFcQZdtBRFURRn0EVLURRF\ncQZdtBRFURRnMNbaX/5ZjmGMeRd4/Ti/zcnA/i5czomK5PHp2NxE8thA9vi6Mbb91tqrf9kniVy0\nuoExZru1dkHa15EUksenY3MTyWMD2eObyLFpeFBRFEVxBl20FEVRFGfQRWt81qZ9AQkjeXw6NjeR\nPDaQPb4JG5vmtBRFURRn0JOWoiiK4gy6aHXAGHO1MWaPMeZlY8wfpX093cQY86gx5h1jzI/TvpZu\nYow5wxjzz8aYF40xLxhjVqV9Td3EGFMwxjxrjHmuMb7/mvY1dRtjjG+M2WWM+fu0r6WbGGNeM8bs\nNsb0G2O2p3093cQYM9UY87fGmH9tvPcuS/xnaniwFWOMD7wE/AawD/gRsMRa+5NUL6xLGGOuBIaA\n9dba89O+nm5hjDkNOM1au9MYMxnYAVwr6L4ZoNdaO2SMyQI/BFZZa/8l5UvrGsaYzwELgCnW2t9K\n+3q6hTHmNWCBtVZcjZYxZh3wA2vtXxljckDRWnsoyZ+pJ612LgFetta+aq2tAhuBa1K+pq5hrf0+\nMJD2dXQba+1b1tqdjX8PAi8Cp6d7Vd3D1hlqfJht/BGz4zTGzAT+E/BXaV+LcmQYY6YAVwJfB7DW\nVpNesEAXrU6cDrwR+3gfgia/DwLGmNnARcAz6V5Jd2mEz/qBd4B/sNZKGt/XgD8EorQvJAEs8D+N\nMTuMMSvSvpguMgd4F/hGI6z7V8aY3qR/qC5a7ZgOr4nZ0UrHGDMJ2ATcbq19L+3r6SbW2tBa2wfM\nBC4xxogI7xpjfgt4x1q7I+1rSYhft9ZeDCwC/qARopdABrgYeNhaexEwDCSuAdBFq519wBmxj2cC\nP0/pWpSjoJHr2QT8tbV2c9rXkxSNEMz3gF/q0+YIvw58spH72Qh83BjzWLqX1D2stT9v/P0O8HfU\nUxAS2Afsi534/5b6IpYoumi18yPgXGPMWY3E4mJgS8rXpPwSGkKFrwMvWmsfTPt6uo0x5hRjzNTG\nv3uA/wj8a7pX1R2stXdZa2daa2dTf79911p7U8qX1RWMMb0NYRCN0NlvAiKUu9bafwPeMMbMa7x0\nFZC48CmT9A9wDWttYIz5NLAN8IFHrbUvpHxZXcMYswH4GHCyMWYf8CfW2q+ne1Vd4deBm4HdjbwP\nwB9ba7+d4jV1k9OAdQ11qwc8Ya0VJQ0Xygzg7+p7KjLA31hrv5PuJXWVzwB/3djgvwrckvQPVMm7\noiiK4gwaHlQURVGcQRet/7+9+3fJKorjOP7+lDmE0FDS0lZYWE0K/RS0rK3NhnBIm2ppiJAGB4Ma\nGsrBlqCMyChzyiEIJfxRWlCSRkMWNESE9A9YUd+Ge4SLIA75WFc/r+W5z73nnufeZ/lwz+F+j5mZ\nFYZDy8zMCsOhZWZmheHQMjOzwnBomRWApCFJtYu0aZF0fbmuyexfcGiZmVlhOLTMSkBSm6SzabtT\n0tO0fVhSj6SjksYlTUjqSzUTkVQjaTgVV32SllzJ97tG0h1Jl9L3VknTkobJXrCea3dM0stUyHRQ\n0uZ07gdJlbm+PkratEx/i9lfc2iZlcYIUJe2a4GKVBvxIPAWaAcaUyHVV8C5dLwLaIqIGqAbuJzr\nswy4B0xHRHsKtItkYXUEqM61fQbsTYVMHwBtEfEb6AGaU5tGYHIlrvNkK5fLOJmVxmugJtWd+w5M\nkIVXHVkty2rgeSrvUw6MA9uBXcBA2r8W+Jrr8wZZ+aa5INsDDEXENwBJvUBVOrYF6E3BVg58Svu7\ngUdkS4GcAm4v6V2blZhDy6wEIuJnqlreCowBU0ADsJUsQAYi4kT+HEm7gXcRsdCS5WNAg6SrETE7\n91MLtO0CrkVEv6R6oCNd12dJM5IOkYVe8wLnm/2XPDxoVjojwPn0OQqcBt4AL4ADkrYBSFovqQp4\nD1RK2pf2r5O0M9ffLeAx0CepjGyRy3pJG9PQ4vFc2w3Al7R9ct513SQbJnwYEb+W7G7NloFDy6x0\nRsmqs49HxAwwC4ym4bwW4L6kKbIQ2xERP4Am4IqkSbKA25/vMC27MgHcBWbInqDGgcG0f04HWbiN\nAvPnrPqBCjw0aAXkKu9mq0x636szIuoWbWz2n/GcltkqIukCcAbPZVlB+UnLzMwKw3NaZmZWGA4t\nMzMrDIeWmZkVhkPLzMwKw6FlZmaF4dAyM7PC+AMc/ZGTHBcbgwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5012fa7c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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QGNsh4Kz647OA5wGcc76ZvV5//VnAkyM+c+R7mqaQTXHNnKnc/sjuWFZ9i4i0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\nUDaUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5012657fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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RZ7zlCxU6sgpc0lrG1OOdc+vMrBv4ANWihtc6535U15Z51F8KuXPTzsH1g3sX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\n8mvRtB/R19ej6/uAs4e9fBr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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5019bb6e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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sN42rPY9WFZlM55CIFjqG+OXOocD6Dm3taEVjPOq4WacoShgey+J8KosrGuL4\ndDiNyfEI6msilQ5cRaH0IEGUAaepJtbr1+6SHb43LmsBn//L1aakjp81t2hyO14r2ycF7Rj+5p8O\nY3AkA0B+bL7nC1d5bkNULnsj5TyrF83SqSJX7DjITPuVahJcDNZ3Qha6CI5TkGM5AcPpHNbtPorm\n9a9g3e6jGE7nMJYLvoqSghZBlAGnT+FWDt+b9vahJj9BayeyJ97ox4alLZ5M5sr5Wcfc2tGK2giv\nqumUMSg1Zut2H827oB9ERhDx9L3e+g+Wy9dQOc99XypURbIeOPwOpmbfiUQs7HifUBRR4Pb/yItH\nIIqeDNVXKD1IEGXAaUrL7PXHz47g7IW0+j7tRKak4brb52DWtDpX3XeN59ces2lqHVIZOeW37Zf9\naoqzIRHB7z4awi+6blAnd0DpftyLp+6Zr5rwOsVs38WNUtMNigehnQcOt16BdveWzL4T/QMjmDWt\nztF1xWMmD1Gx4Jvx0kqLIMqA06dw1utZjuHGlNSew5+ge88H6uRnp/tusfO/fPRMvlA4jWfe+RCb\n9x3Xrzhs1Ji5IShqPCdpP6dO+U6uMR4JYatBWap8Jxy3PTFr+pkOfnqQ1IMEUSZK8chTHMON9VFW\nAo9UVihJzVbguxfh0bz+Vaaabng0C3AcvvW8PaWhHRQ13pT6mCqCODWUwtRJMcSj5UsS+WnK61Rx\nKAgikhkBiZisKN37/hl0LLjS8Vjka0qjq0dv/tuYiFVSiEHqQYIIEooqUJaxFw9c2hRYfU0EAFAX\n4wteY5aSKlXNZkzBWfkrhngeP3nnBDYsbdH5Jm7taHW9pxOPhjBtEsuLsRU1YXfybDcyb6t7bHY8\nu+dx+hmFQjzqYhxSWQGzptXhssmltD2JVWXbE1/TgxzHfYbjuJ9zHPd/OI77Pcdxn+c4roHjuNc5\njjue///J+ddyHMdt4ziun+O4IxzHXac5zj351x/nOO4eP8dMEH7hV7rLLCXltZrNKsUZj4Ww7Zf9\n2PRaH7rb56DvsdvR3T6npNVIKiNg1aLZDBFEr6sC5VLuv/EeA8DIWA7ggE+H01j9s171eIIgFj2P\nYg9lmqaz+Iy8atbpZdPPcuJrepDjuOcAvC1J0o85josCiAP4LoAhSZL+G8dx/xXAZEmS1nIcdweA\nvwZwB4AFALZKkrSA47gGAAcAzAcgATgIoE2SpPNm56X0IOGUchRalrt9hx9pLbP75Me1iaLkquWL\nGV6N0aoL6sLIAAAgAElEQVSI+txwGts72ywLsrXvnzYphjWLmwuaclba1b9CVDY9yHHcJAA3ArgX\nACRJygDIcBz3NQA35V/2HIA3AawF8DUAOyQ5iv5rfpV2af61r0uSNJQ/7usAbgPQ49fYiYkFe3LP\nN/dzmYZi4XfxqRE/Ot+aqfa03ZGddkS2OtfImPOWL2bURnhVBak4jLx89Izj+68tMwCg1tB1t8/B\nV7e9XVRtaHy/KAGPL5nrS/PP8Yif6cGZAM4BeIbjuEMcx/2Y47gEgGmSJJ0BgPz/T82//jIApzTv\nP53/mdnPCcIT2IW/vRi4kPZUreZ38SmLcqWA/Kqdike9qX1SHky0bVPW3NqMroVNju+/2cNH09Q6\nfO6qBiTze39atJ+z8f17Dn+CRZt/BQBVlaarFH4GrTCA6wD8UJKkawEkAfxXi9ezPinJ4uf6N3Pc\nCo7jDnAcd+DcuXNuxktMUMwmoSsa4p72WjLuCa1eNAtP3i27pmvbXlRrOww/AqRXwTCVFbCyp7fA\nYeTeL17NDIBWn4HZw8epoZQaUK0CbSUeXsYTfqoHTwM4LUnS/vy/fw45aJ3lOO5SSZLO5NN/A5rX\nX6F5/+UAPsn//CbDz980nkySpO0AtgPynpZ3l0GMd6yKNr1M32kn4NoIj8FkBg89f1CXTmuIRzCU\nytrahwqg4akv2C0ktrofZg8mdTXhgr2xYnuB7FSoPp1slZb1I5Xq5F5UO34LMd4G8E1Jkvo4jusG\nkMj/alAjxGiQJOk7HMd9FcC3cVGIsU2SpOvzQoyDkFdtAPAeZCGG/huogYQYhBOKbaz7IZQwEwUU\n28S3GnOlN/ArOVEWux9W99tofmtHsFHqtfp5r4L43bCJrcH57Yjx1wB+ynHcEQCtAH4A4L8BuIXj\nuOMAbsn/GwBeBnACQD+ApwD8FwDIB6e/BfC7/P++ZxWwCMIuSgoIHJCIhfBUZxuOff92PL5kLja/\nLgcsP4xYAWsfOTtijaC1jWfLydNIZcqT3ix2P8wcRp5558OCfUs7gplSU6F+7jUG7bvhNb4WF0uS\n1AtZqm7kK4zXSgAeNjnOTwD8xNvRERMZs6fR2oiES+pj2Pz1Vl9XC2YpyaRFAa9OrVdmJWIxWIq6\nrp5ePL5kLhKxsO9P+cXuh5Kykzsvy24SSp+vd08M6VZRrM+ma2GT3JIkFq5Yus2vguVqg7wHiQmJ\n2dPoaE4si9rOarPejlouaJv5XolZ3IpQ7NwPxfy2ef0rWLzlLdUM2DihswQzy6+fgRU7DhYtFvZL\nPOOkMDpo3w2vIe9BYkJSavdbT8ZQggVQ0PYtzPaBlNolO/e1lGuy+167BcZG30e7xcJ+fRZOCqOD\n9t1wgK3BUdAiJiTldqfwgyApxLwQs7A+k9WLZuG+L11tKy3nV7Av9oDjROThFqcPWUH6bjiADHMJ\nwoxyyI7t4naCKVdPKTuoMu/O+YjHQjg5mCoQsxS7TmOKsX3edNx57eVYseOgrQBj5364cQkp1gvN\nfA8pjMFkxpMVjtUY4pEQ874G5bvhNbSnRVScchXTas+TygpoiEd8735rZ0xemuhWsjCZ5znU1YQB\nCaqYRbmvAIpep3Ev5uGbm2x1DHY1Tgf7lm6LhfsHRlyP1/g51oZ55hhqw3wgeo6VE0oPEhWlWLrG\nqzRHUPP8XqYpg3qNgP3aJ+34+x67Hc3rK7vvqGD1PbRKjb589Izj8Zp9jg3xCEZzom4MpfZMCxiB\nqNMiCEusakq8XIW4qV0pddVi5/1eypODXJ9jt/ZJa9mUylh7+JUTq9WZVk6vtGRR5PRuxutE2Tre\n5e0sKGgRFUX5o2ufNx17V92IP/zgDnS3z0FthHc8CVsFCad/3KUGTLvv91KeHOQJzO51aoNDIhr2\nxCy3HPC8PN6hvCnvy0fPuB6vk89xvMvbWVDQIipKKiOga2ET1tzarHPgHkxmUBvhbf/xFgsSTv+4\njQFzSn0Mybx7hp1Vl92Aa7cuyw7aa1QeAvoeux3JAJjuurlOv5zj/cIzc18H31Uvvz/VAu1pERVF\nWR099HxhHYxdHz6g+J6Jk30Cnud0EuP2edOx5lZjy3frvSJBFNE/kCzo3cTa39Dtl6QF8DxQE2Hv\n4dnZW+nZ/zHuvPZyR+MtB1Uqwy47Tvcmx9F9pTotojqwqkEZGZOtc/oHRrD3/TPoWHAl2/HcRh2L\n8Y+7NsybOqprN7j3rroR3Xs+sL3ZLYoSPk2msbKnV7cx/9Kh07j/hpmmG+R2RCnFJjNRlJDMWBfD\nTmSqZYL3epxVct0kxCCqA7N0yMiYvAJTUobLF8xAQzzC/GOza+Oj3cgezYmmKTxt2qVpap2jvSKn\nvZu077NKKdpJOSpWRX7sbVVrny+FUvYpy33tXhrqel1WUWkoaBEVh5WX39rRimd//aFugl7Z04vR\nnGj7GMVy+0r79T/84A7sXXUj2udNVyd37f7EqMP9MMveTRaTT7ENeLsb9H5szo+Hic+turLarz3I\nqlI3UNAiKo5xA/vJu9vQEI9i2y/7da+zWi043QS3bL+eFtSWJQBQE+axdXmrPqgub0VNiP3n4zZo\nFHuf3eP6sTk/HiY+t+rKSl27V6s7O9ddTatoClpEIFDSIamMgIeeP4g/nEs6mvid5uytUniCKOqe\nqlNZATt/exLd7XPUOpydvz2p1pIZcRs0ir3P7nH9UN0FWU5vF7cPE5W4dk9rFItcd7WtJEmIQQQK\nRVBxx9xLbSv2vDZB/cZT+3Uihj/84A6mM0PfY7djNMv2fgPgauO7WPD1u+Ot2bHduKO7HZ9f1+jW\nMaQS5srldEoJkHk0GeYS1YfyVKj0Oupun4OmqXVIZXKmjtnsBoSHLP/oTA1I00LBU3X/wAjztf0D\nI5g1rQ6DI+wJwY1haTGjU7+MULUT27RJMaxaNBszGuMYGcshHg3ZMhj2wkbKTysqN2a5QGXMlb1c\n3RW77mpbRVN6kPANN3lybQrs5aNn0L3nAwwlM5YtHtz80Zml2ngeBamUve+fwdYO/Z7WhqUt2Pv+\nGSTTuarf6wEuBv4p9TGsvqUZ63YflVNFO+RUEYCiKUcv9n783j9yo8pzkm71am/IazGN1XVXm6sG\npQcJXyi1oZ+T9JDb9AbrPACY455cG0EqKxTUjDUkImhe/2ogTF1LQUmX/qLrBkc1aaxjlHIv3BzD\n7vfF71olpwXsbo7lR4F4gIyWKT1IVA4nKTvWZKK8xqxXkBY36RurCcwslVLHc0hlBcyaVofLJs9U\nx2bVa8lPvJyEladtpzVprGOUci+c9o0C2A8ZxgnXbmF2KfdzLCcgmc7hhW8uUF1QevZ/jOULZugK\nze0EBLepTDeU81xeQCstwhfsPjFbTSaAvQlJOY7dCcfLJ8tKPKWKoiRfY77Z4pZ9x3D2Qrqk8yrX\nkUznsG73UXcrLR/3tBriEaZ7SW0khAd3FF9lu7X5sjt2+f1pdBlcUEI8sObFI0EQOVQDZONEVA67\nKTur1wFwrVgDzNV7XqulymmR40Vbe6tjK6uFLocrA+0x/FAPKrZaU+pjePjmJjRNrcOpoRSuaKi1\nTM9qj3X8rLz6UUQ+2teV+p0wfX/nfLR+77WqTx+XCUoPEpXDbsqumIjCTlGkcRL/0V3XISOIphOv\n12qpcrY2Z6Vd1+46gu72OfjqtrdLUnzJ9yaMmnDIdarIi3vBOkY8GsK0SbJIRFsGsbWjFV0Lm7B5\n33H1/dp0IivAA9D1uqqLhUv+Tpi+PxaqWPp4vELqQcIX7CqurJRLyTS7CWAynbv4foba7Hwqiy5D\n4bDOw6/K1FJazCbHpql1tq+hmMKtFN87v5wVUhkBqxbNxtpdRwqsve794tX4/MxG3Nk6HW+uuQk/\nfXABIOXb3hi+G2t3HcHDNzcVFGZbfSfsXJPZ+wdH0tiwtGVCtQ7xGwpahG/YmfysXB7i0RA2LZun\n+92mZfN0T7+sSfyKhri1h18V9yAymxxPDaVsXYOf7gd+HjseCWFGI/tzrasJ45l75+PRr/6ZTqof\nj7ED/KxpdQUPUWbfidowj8FkBj95+wSOnx1BbSSEkXQOgqD3wGS9f+OyFvzt//o9Nr3Wp7qpbO9s\nq3iLmGqH1qdERbFSLqUyAmIRDo8vmYsrGuI4NZRCLMIhnRMRj8rPWyy12amhlGVKJkhqKad7QOy0\naysSMTmtZyU+Uc6TTOcwpT6mW4V6IQxwU+RtF57nMDKWY36uJwdTaEhE1dW1cu6Tg9bfA+PxWd+J\nVFZg9ifb2tGKSxIx9X4XvD8tYP1LR9X9sz2HP6G9LI+glRZRccxWZKII/PU/9uKmTW/is999GTdt\nehN//Y+9EDUPuawn3MnxCLYZioGVp2YlzZPKyv20Upl8wDDxEfQTNysTdto1hrhF8bXxPOt2H8Wa\nW5vRPm86AO/cD/x2VohHCz/rDUtbsPn1Y8x2LFv2HWN+D4yrUSX9p8oAJKjfw3g0hMXXXMpMSxoL\nnrXfY3DA2Qtp3e+rJQUddEg9SAQWJ7J5RQKeSufAcxxiETkgJfImvMaGj10Lm7D8+hlYudOdSs4L\nyuX5Znae7vY5WLzlLc/OqT1P+7zpeGRxMy6bXHuxG7PFStAMVuPO0ayI2mhIrYXac/gT00adT987\nH6KI/HejcBx2fPlqIyGm92SxgmeWQCjE8/JYAl4LVSGoCSRR3djdHE9lBAiiiP/+/x3HUDKLB547\ngOb1r2LFjoMYHMkgHgkVNHxcfM2lWLnTXKxRDsrl+WYl3vByP09Z9a5eNAtrb/tTfOfnR9T9paFk\nBsNjWUerWdZKdCiVBc8Dd/14PxZveUtNv7GstrZ1XItYiMdoVsA3ntqP1u+9hgee1a9mTW2jMnJ7\nmtowbyoISqXNvyvGFfHT985HRhDx4I7qcFIPMhS0iMBSbHNcncx2HMBwOodv/IcZECUJL3xzAX7R\ndQOm1McudiI2TNylOD94hR0VoxdqPLPzjGYET9qWKCgT9X1fuhprXjysCwSPvHgE51NZT3wIRREF\n34uOBVeiMV6oVk0LoupSoftO5O+xWUCvjYbUIBkLcQX91DYuawFfZPbUpgtFCZaKVsI+JMQgAk0i\nFsJTnfPV9I6y/2Tc8N998DSWL5iBdbuP6mpyNr/ep6aWtJvyZs7t5ayfKVbL5pXbRjwSwo/uug7n\nU1lV0DI5HkFthJc7QXNyas+LdBXPc8z9pd99NIQrGuJwokGwqn2KR9m1ZHX5xpyKy4Xi8FHwnYiF\n1NSjmYO/KiTpnI8fvPx7teNA/8AINu3tw+avt5Z+LQF1Ug8ytNIiAokyYT/w7AG0fu81fOOp/RjN\nsp+O2+dNR+cXrmI2dVy1aLY6qWmfzve+f6bg6bncsnc1hdSZXx10zkcidvH8XjqeZwQR63YfRfN6\nWYiREUR1D8rrdJWVLN+JEMFqJapdxdSGeSQz8mp0eCyrytHl+8f+TpwcTMkrcMZqfsPSFjzxhtw1\nWwmSZy+ksXjLW/jsd1/G4i1v4eyFtGfXQjiDhBhEILFr79Q+bzrW3Cpv+JttlkOSAwRzU9+h+7bX\nWHovcvDE8VyxQDLey8eXzMVNm97U/cwLQQbLh2/jshbUx8Kor4l42ltLEEQMJjM6Qc3W5a1oTETB\n8RxW/6wXf3VTk7pC+uGb/dj89Vas/lkvNn+9tcDq6eRgCptfP6bulSlWTKP5Bwg7K14n3QOoZksH\n2TgR1YtlOkWCmlZ7+OYm1cbIrKljXY38NWfZA2nTSZXAqrYJgKMUpukkXxc1TdcZf+ZFukpeQcZ0\naV036kE79XSprKAKagD5/q3c2YvtnW0I8RzWLG7GIy8e0QXPwZE0zl5IY2Qsp0rblXRiIhbGueE0\nwjx3MV0bNU9HAvogNZYt9G7c2tGKxng0MLWB1Q6lB4lAUiw1pEwAs6bJgoon3uhn2+UEfM/AKjg7\nde4wSyeaqd9ODaUKfqa1yCoFnudQV5OvvasJW9aRFT2OhauK2f5ZIhaGKAKPvHikQBCSEyRsWNqC\nZ3/9oS7VamU9xhqHKEoYGZPruz4dTmP1z3oxcCFdkJJc2dOLZD4N6NYei7gIrbSIQFJMpKBMIiP5\nCVlJ5yib5alMzrLbsRG/3MmLHaNYDyonT+dWAZDlogFJTn9pRQqsIF9OF3unKAHZeP+S6ZxpQJv2\nJzVYtbMXLx89g29/ZZbu93YNf1kp0E3L5mHapJhpEE1lySTXC2ilRQQSu4a72tXIy0fPoHvPBxhK\nZhwHrFI989weo9hqyol5ram0PSsW3MtELIye355UPfG62+fgpUOnMZrVe+r56SfIwqnEPx4JFQhq\nti5vBQeoNk5aPndVA46fHdG5vLtBNuPVr6jWvHgYSZPPoH9gpOCBwC9z4fEOCTGIqsfpSsD4ep4D\nHni2NGeKUtwtvFrJOJHI233tyFjOVpNFL3Ar8RcEEams7H6STOcQ4Tnc9+wBLJ4zDbfPvRSrduoF\nIZv29pXeNNPCreXT4bROGLJhaQteOnQa998wU71npZQzBHnlWyIkxCAmBk56OLEni1ZMmxTTvc6p\nKKGUOhyv+nE5MQK281pRlFSn9PZ509Xmi/0DI6iNeJ+ksRKlKCpI1lhDIR71eUFNfU0EoiRh2qQY\nFv7pNPwsv5psmlqHZDqHaIjD5q+3mt4buwEhlTZJ66blFOCTd7chEQujf2AELx06jY4FV+r2It2a\nC1eiUzZrDJUMmpQeJCYUbLFCL1Ytmq17ndPUUVDqcJykE4u9NpURcHIwha6FTVhzazO693yA5vWv\noHvPB76kCE3dKSI8I0WZRirDTq1pe29t3ndcra966PmDyEkwvV67qVBRlMBxwMZlLYUuGRwgSBIS\n0RBGswJmTavD/TfMLAgqbh9yvKzdc0O508UsKGgREwqzyWJGY9xVobGyL1Eb4Zned9XQo4uFssra\nsu8Y7vnC1bZczkvFKvCzHjQGLqSZE6dV7y0lKOi9K3OqCpDVtsV4namsgKffPoH6WBiPL5mLvsdu\nx+NL5qImwuO7/3wUK3YcxFAqa9lFoNhDjtl+V6WdNSodNAFKDxITDFO1XlpwXENjTNV0LWzCk3e3\noa4m7HvaxG6Kxm0qJ5WvN1q1aDbqa8Pobp+jOqoDPhn7mihGrWyhWD3BlN5bXQubsPiaS9WU5t73\nzyCZt6tSHP+nTYoV1HJtWNoCQO6BNW1SDJDkPSyl3kxpV5LJO28odd7f+5+/V+9PV88hPHl3Gx56\n/iAzjWeljrVKAZrZTpXLfqzSQROgoEVMMEwni+jFydzuH79xX2LzvuN498SQLyIFLXb3NUrZ/6iN\n8Pj3lFTg2wdAp7yzc512A6dpI0aTB43+gRH138rEqZyrNspj+YIZWNmjd8p45/g5fLFpivq57V11\no1rLBUC1eupunwMAWLO4GQ/uOKAe4+//ch4kKaPukfEcB0kCFm3+lU6UocjczfasrPYUR9I5y709\nq1IQvylWolEOKD1ITCjsSuntUKmnTrspGiepHGM6KpURCpza1+46godvbnKcPnWyB8LaZzNrZa/4\nAwIXV8uDyQx+8vYJDI/lCrwoV+7sxcwp9bqVm5nb/6xpdfje1+YUFCf/zT8dRlaQ0Lz+FTz0/EEI\nooTRjL54u33edOxb/WVwHLB31Y2mzTbN9hStvldefn/d4LTg3Q9opUVMCHRP+3mjVGWycEulnjqV\nSa2Yos9uUGWtyH764ALTyVx54rebZnSjktPCamUviGKB3RLPAz37P8ad116O+pqIaQ8xrcO/mdv/\n8bMjpgFNm5ZULKO2drRiZU+vZbrx3HBa/W5YrT6Lfa9KVZuWov5zolD1C1ppEeMe7dP+6p/14tPh\ntNyOY6y0gs5KPXWmMoItRZ9dRSNrRWZWmKudOO1gFThZYgMzAYJuVVIjG+8aVxs1EXmvae2uI2ow\nMo5f2dtSRDM/fLO/QAWouLwbj8FaQcnXEsbBj4awvbMNj905t2B1tnbXEay+Zbb63RAEEZ8m06ar\nT/b3qhU8h5ILkb1Q/zlRqPoBFRcT4x6l8HdKfQxrbm3G2l1HHO/xmFGJmhVlYn/o+YOWRb+2974Y\nhbJ3tk7Ho1/9M51NkZt7ZVZ0/fS985FMG53TWxEN8fjWC++5KrhNZnKIR8NoXv8K7ph7Kf6fr/4Z\nkhlB7SGWiIbQ89uT6FhwJRriEdXhfywrQBSBeCyE42dHVMGJ0kFg7a4jpiuolw6dxn+67nJIEvDS\nodP49ldmmRYdQ7p4T+x8dur3Kr+ydHNf7H4efu/D2oSKiwkCuPi0/4uuG1TpNuAuVWXEq8Jgx+es\nYSvq4tGQrqGjWSpHOymy/PvOXkgjEQuXnAYyEw6IIhhpw148vmSu64Lbnv0f454vXK2ujjKCXkiy\nraMV37xxpuo2rzj8x6PysUfGcuje84F6/j2HP0HTlAS2d7aBA6dzBlFWUD+6qw0j6Sx2vXcad157\nubpCNUvtjRg8EbUp3tGMLIvXGvSKogQJEp77zUe6JpQ9+z/WOWzY/jwCoP4rFQpaxLhHSZOZ7VG4\n/YO1WmX5vQIbywrYt/rLuKIhjv4BeXVwbjiN42dH0L3nA92TuDGosqT6W5e36qyHtnVci1iIR1oQ\n5Y7Rms7RjmyGsgIa4pGC4AcOnrVL0aY3J9VGsGV5K0Y1QhLgYlB86p75puPneblgWLuaWtJ2OUI8\nh5oIe7Kvrw2jvjaMzi9chR2/+Qj955LYsLSlYDWvpIzjUXk197mrGkxW/q1IxMKoCV/swTU5HsGd\n116ue92GpS2uXEmCoP4rleoYJUGUgPK0f2rI+inYCZbNG+Fvwz9WG/mNy1oQC/H421/8vugKhSXV\nB4DtnbL1kNIgcySdw3A6p5vEt3W0ojERU49jDMqCIGIwldFJzdVr1whfRhirO7N2KcU+n9oIr1uF\nvHL0DDq/cJXjB5RYiMfkeFTtA3b238cQj4ZQEzaX3Z8cTGHR5l+pgWTTa33Y9FqfOp7RjD7QpzIC\n9r5/BhuWtkCUJMbKX15tJmJh1EZC6Oo5hB/edV3B69buOoLtnW2or3EWuCotmfcCEmIQ4x4lTTZ1\nUgzbPHKtsJKT++0awGoj/8iLRzCWE3XFv7UR3rarwrZf9iOh2VwfzYk4n8oWiAq6enqRygjMzXxB\nEJHMCAVSc9a1m4kNJscjjj4f5eFBK0hZ+KfTcG447chWSxQlDKWy+OZzB9D6vdfwjaf2IxQqLrvf\n/PqxgpKAPYc/weItb+GuH+8HOOjtmyIhdCy4Ei8dOm3q2nFFQxxdPYdU30czJWTCxcqo0pJ5L6CV\nFjEh4HkO8aicdvFCrltsb8DPfQOzc0//TK36766FTXIbesaKx46rQm2ExyV1MbzwzQVq+nHP4U/k\n64iFCvZ3unoOqSs1O9dutt8GwNHnk8peDJLKWNbuOoIn727Dto5Wg5DkogKvQGbOkOavzKcT60I8\nU3a//qWj6kOCcp1NU+v0XY8jIWa69P4bZpqa7vYPjOB3Hw2pvzeT5SfTOdTXREzvjRmV2If1Elpp\nERMKL+S6Ssda1pN8Ml+Y66d5rtnxTw2l1FXAvV+82nTFU0yqr8qidxxQVy9rbm1G+7zpahGv2ZO/\nmdScde2sz8Lp52MWwOtqwmhMxC6uKDrnIxri8cCzF1eHw2NZuexBkgAJTKd/7WpVW98HTharFF5n\nTreCAVCwKh1KZRGPhNTmnCy5/eeuagDPA9s6rlXTicbXWT0EjedeXbYk7xzHrZQkaWuxnwUFkrwT\nfjKSzuEnb58o2BzfsrwVl9RFwYHzfU/LKKS494tXy56HeWuhmqhevg1clF7zHGcpFDGTRct7LSEk\nYmFm/7HtnW145p0PC+7L1o5WXJKImV67HdGK2WvsSriNr2ufNx3fuU0vYd+4rAV/92qfer9WL5pV\nYAXldN/SSvIvSlDVm/FoCKeGRrFl3zFdry8ASGZyqI3IqtD6mohaa2amHgxC+xKX2Bqc3aD1niRJ\n1xl+dkiSpGtdDs5XKGgRfqLUNd0x91KdI8VnpyQwlhOLOh64OqfheLVhHqM5UW3boZ1YtY0OFXHA\nnsOf2G9KadHgUKk1Yk2KDfEIhlJZ9Oz/WDWqTaZzSERDCIXYSR07E6wXohfjNe1ddaNO3g5cDMyK\nsEIxvDULiLaCre0auLxqMMJWojoJQgGvxbKi9KDFcVwHgP8LwJcAvK35VT0AQZKkRaWM0C8oaBF+\nYjYpPHl3my8OAcVcv1lj6W6fg8Vb3lL/2yiDd3N92knP2C04HpEDk9NgbedcVq+JR0IYy10sDjaT\n5RuP8Ycf3IHm9SaBGVBbipgFb56z9xmzxv7mmpuwbvdRR0FFEESkc6K8OouFkErLhdRMZ3+Lhw67\n464QtgZXbE/rNwD+HsD/yf+/8r+/AXBbKaMjiEqj5P0FUcTwWNZ2/p+1J7S1oxUJixomsz0GO3sP\nikhgSn0Mv+i6AS98cwGS6RzGcoLpnk7T1Dr1vxW/QLvpIbPrqw3z6piHUlms2HEQsx99Re0fpRTG\nerEnpd2vsXrNYDKDB569qPgbNVFoGq9JKX/Qouy9KWP3Ym+SdS+L9foyonxHhlLyPuPsR1/BgzsO\nYjCZZn9fAtKQ1C8sg5YkSR9LkvSmJEmflyTpV5r/vSdJUq5cgySIUjEGB0EQVUfwP54fUydgO15s\nLNnwJYlY0RQYSyJuxwcuHg3JNkIar8F1u4/Koo80e4JS2na48QvkeQ6TayN48u429D12O7rb52Dn\n/pNqYPJS0m82wWp9Ic1ek9S08Cg2Du1n1vfYbZhaX7z8wUqwYlfowPqumH1mZkEllRXMyw8Y1xoE\nJ3Y/sbuntQTABgBTIS/hOACSJEmT/B2eOyg9SGjRptemTYph1aLZmNEYx8nBFEI8h+/8/EhhqqZz\nPsDBEycLs/TW9s42rNhh7UGnvP/T4TQzpcTy8NPuabnZgC/mbehF2kyBVYysePopQgOz9GhDIoLm\n9d6MrZ4AACAASURBVK86GofZd8EsrchKdwKlFY8rDytaB5Kty1vRmIiqDz6imJfl51OetVHe0bVW\nwhPTAzz1Hvw7AH8hSdLv3Y+HICqDNr22+ha9bY5ZC47aaAh3/Xi/J6ors/SW3Zomq/bxNZGQvvYs\n311389dbXU9Wyl6V2di8tAIazYloiEd1jhabXuvDy0fP4NtfmQXAojmkiy6+xnqsl3ovClTMGlMa\na5rMmjRqHUWs7vtoTsTO357UXfPO356Ug3R+X3AwmdYJNbYub0XXwibVvaSUe17t2L3asxSwiHLj\n1dOilWGumcFp/8CIJ4a6gLnf24XRrK1JV2kfb/VadWKtufg+szEXu69afzzW+by0AlLOxVLyae8D\nK3jEIyH86K7rcD6VVZ3cJ8cjluPwwjDW/BhhzH70laIrr3g0hG2/7NcFoDDPqUFa63gCQO3b9WRn\nGwDZvURRHGpr65TPdCwr5FOnpTn0BxW7xcUHOI77GcdxHRzHLVH+5+vIiAmNF31/FKwMc7fsO1aw\nt6EUeALeOFnIk3zhOf6l94+2baVYhahuAoWd+6r1xzOKMYzu8aVaARU7VzEygoh1u4+q+3wZQSx6\nvlJFCmbH6B8YsbXHV2wMpivzaBjLF8xA32O34anO+WjM174ZP9OBC+kCmy8vbcQqjd09rWcYP5Yk\nSbrf+yGVDu1pVT9e1poof9SKyWzBvtA98yFIEhKxME4OprD59WO6AtP7vnS1rbSP9nzGlcxYTsDA\nhXSBK/umZS0YSQuYNa2u6PG9WHnaua/aVh92663cUsq53HxHvCi8ZR1DWw8HFN9vshqD2XUppQvF\nCqet5PzjQfJu96+fB7BSkqR/AwCO4yZDlr4ThC942fdHWRkkYiGGH921qNH0mErEwmob966FTVh+\n/Qys2HGwwOXcKrCYFd4mYmHc9eP9uoluw6t9ODecttUzaiwnqMW9yv87DWR27ivPc2iIR9RgrQQR\njpMnVLdB02ysjYko7r9hpvpzu0pHN98RL9rFG4+RTOfwzDsf6nwIrfabio1BWZl3GcQpm17rY+95\nGu6DmVfheNn/snsFLUrAAgBJks5zHBdINwxifOB13x+dYW6+9YQiWtC+xjgZadV9ak+mzvm6vSPd\nuBnGq8q+WGPiYtsLeUUnByw7TubDY1lmmxCnnX7t3FelDsurrsLKMa1WF24MXN1+R7wwjNUeIxEN\no2PBlXj3xJDtPT6rMcjfwxi2d7YhHg2r4hTF1cR4fcb78MQb/QV9wSai5P0wgJskSTqf/3cDgF9J\nkjTX5/G5gtKD1U+xSc5NqkwrIz45mCrwebNjwVNUUm3jPW5cI8wk748vmYubNr2p+1mp6TEr70En\n5zJeg9fWQn557Bnl5jwPtdux5Xs8lpjbvT7W635013UI8bx8DRNU8v73AH7DcdzPIScm/hLA910O\njCBM0f7x10ZCePre+QV+bG4CGlBYW6OkXMwUgmatI1JpoWClpT3nvtVf1u2LGZ/+nT7px6MhXNFg\n3nvJ+DMn6THFrFV1MOc507RbsXNZTdx+tHnXXktthEcqIzD3Hp0EFJbcfOOyFtTHwqiviVh0Pfa+\n3YfdVGax142HlKAWW7uqkiTtALAUwFkA5wAskSTpeT8HRkw8CpRtOw4gmZb3cbT7HFaODGx1XBpj\nWQE9+z9Gd/sc1eXhpUOn8fDNTaaTp9J+XadqW96K2ihfYMWkPee63UfxnduacWfrdE/cCFIZwdR2\nyKzTrxVKU8PBkQxW7DiI5vWv6lSEVq1PzM5VTJXol7WQci1DySzT1cSpCtWsweb5VNa1+s5pmxDt\n67XtUKz2+rxouVMt2EoPVhuUHqxO7KaQrFJwqQzbQPapzjYMJbO6wuINS1sw/TM1uPvp3zIdMJS9\nJKUOaCSdw3O//lBTJ2NtWqtVJZaSovFyT8vOvY5HQoyVrPW5in12TlJ5ZivlVFZgrqjM7v9T98wH\nAEdpSbPvVt9jt4Pj4Fh95zSFWcVtRbzA0/QgQfiO3RSS1Qa86TFiYTxoEFWs3XUEP7zrOmxc1oL1\nLx0t2N/ieQ71NRGEQjxGMwK+9bxRlHFIFVYYzzltUgzJjDcFnspTdCTEa0Qksss34KzTr4LVveY5\n512Fi312dlNdZvszGUFEz/6TBb26FDsnq3M7SUuafbdODaVwSX1M//BkI+1oJcxhBU2nr5+I+N65\nmOO4EMdxhziO+1/5f1/Ncdx+juOO5wuWo/mfx/L/7s///irNMdblf97Hcdxiv8dMVAa7KSQrF3LT\nY5h0251UG8HfvdqHl3o/YRZhKgGDFZjkYBhSXTW0rFo027MCT0XN98BzWjdzUTc+p2mhYvfaaVdh\nO5+dnbGyUr/nU1l09fRi8TWXqo4muntqcW6naUlWIfjGZS0FTht2045O9/L82Psbb/getACsBKC1\ngNoA4B8kSZoF4DyAB/I/fwDAeUmSmgD8Q/514DjuzwEsBzAHcjuU/8FxHH2C4xC77tRKHRHLhbw2\nzDOO0Yp/H80wJ6/jZ0d09TVmE4TZ5KcUIxsdHZy2n7DCS1d1Ba+dwL06HmvSVkQoLEcTxcPRuPeo\nWBw5HZciN3+qM+/20TkfDYlogQjD7mfiNGhaPXQ52Rcbz/i63uQ47nIAX4WsNFzNcRwHYCHkxpIA\n8ByAbgA/BPC1/H8DwM8B/Pf8678GYKckSWkAH3Ic1w/gegDv+jl2whucKLfsqsEA2XTU6EL+7okh\nZj1UJidi18HT2LC0paAN/M79J3VjMKvzYfvtteL7v/i9GvQUA9TRjIA/nh/1rM7Mb+WdFzLtYsez\n+z1gpecUEYpZ0azy4KDc/1NDKSQ0Kzmn18nznKoONavHs/uZOPVpZBUWb+tohSCKrmvkxht+J0m3\nAPgO5E7HANAI4N80vbhOA7gs/9+XATgFAJIk5TiO+/f86y8D8K+aY2rfQwQYN5vKqrKtyPusJg2l\nxmYsK+CSuhhqozyWL5iBnfsvOmsr3XbtFoWyJmWeA85eSAMA9hz+RC3+7G6f42mBp9eF1tpr8lKm\nbXY8JyUKPIeCSXtyPIJtHa3o2X+y4MFD++BgtFDy6zoB+5+Jm4eDaIjH40vmqibAkRCP537zEe1z\n5fFNPchx3H8EcIckSf+F47ibAKwBcB+Ad/MpQHAcdwWAlyVJmstx3AcAFkuSdDr/uz9AXlF9L/+e\nF/I/fzr/nl2G860AsAIAZsyY0fbxxx/7cl2EfdwWlNpqwT6Ww4M75Ne0z5uOh29uQtPUOqQysqWO\nUeEHgPmkb6VUKzbJsCZjXS+r5a0Yy4mY/plapDI5JEzaoxej2hVlTpWKrMJYgK0e5Dngx2+dUH0L\n+wdGsPf9M2ovLr/w6zOx8h1cvOUt9Wd2vASrsKdWxdWDXwTQznHcHQBqAEyCvPL6DMdx4fxq63IA\nyobCaQBXADjNcVwYwJ8AGNL8XEH7HhVJkrYD2A7IkndfrohwhNu0lj1/PLmGavfB0wWKsg1LW9B/\nLok9hz/RPZGynraNT+FOJqOCp+i0PIn+/V+2on9gBH+bXwGUalbq5Gk9iBNVsVWxUS33rRfek/tb\ncZzus1L+u76GV/8tCCKWXz+joKFibdjf7Xqv06sKZveqaWqd7mfFVtrV/qBjhW+frCRJ6yRJulyS\npKsgCyl+KUnSNwC8AeA/5192D4B/yf/3nvy/kf/9LyV5GbgHwPK8uvBqALMA/NavcRPe4bag1M77\naiIhbNrbh84vXFWgKFu76wgevrkJgPO9H6eiB50iriYMEcBdP96PxVveKnDEKAU7yjs7ijanha5m\nODmO1efp5MGGdc7RnIiVO/UqzZU7ezGas25R4gVKKlu5DqW4vRTM7lUynXMkcvFDvBMUyqEeNLIW\nsiijH/Ke1dP5nz8NoDH/89UA/isASJL0AYB/AvC/AbwK4GFJkqr/zk8ATKXpkUJHCe1kxFYA6v9I\nUxkBZy+kUV/DrtFRnkydBoxSRQ9eq/KcUGyi8qpHmdPjWN0Tuw82ZuespETc7f20Cvhm9yoRDTnq\nX+bmvnj1QOM35IhB+Io2XTUylsOzBkeJhniE4Sgu/3w0J5qmXor1yFJ6DzlNidhxdiiWfqtUiq6Y\nWa9XprVu+1iZ7SnaSWOZnXN7Z5vOid/tNbn5zPzq51WuvmlOx1UGbJ2oEistYgKhpLVSGQEPPX8Q\nm/cdL1gFaFcHU+pjSKZz4JQ/FIPvoPa4jYkopk6KFRSDbu1oRdPUhKOOuspTZjwawpN3t2H1olkF\nqwK7T9aV8oFz2xHX6arEbR8r1j3R7g1ZrSKszlnqytbtisnNfUgxPDB79n/MLGgv5ftjXLGtXjQL\nT97dJj88MlZR1ZROnHh6SaIimLYQj4XVn7fPm441tzYX2PSYBR7ZkTzfI4thOQQA4OSnzuLO3vqn\nzK0drXh4YRNGs6L63pF0Tp1wFKVaz/6P8c0bZ0KUUHHxQ7GaIK+k8370OismSTees33edKy+ZTY4\njkMipumR5uL+u7VOSqZzzPuQTOdQXxNhvqc2wjOFQ7URb9cPxprHwWQGDz1/0PTvqpqcOGilRZQF\nqw1m5ecP39zEtulhPO0pKyNBFJHM5AoClnNnb/1T5sqeXoxmRd2TrjLhdO/5AM3rX0H3ng/Qcf0M\nJPOpmFL2iaywu9dQbNXimWtFBfbttOe8s3U6vnNbM9btPorZj76CB549gNFsYTcA28cuQeVqdELZ\nsLTFeqWVEZjCoVKFOiyUh4HRrIiVRSzF/HLh9wPa0yLKglUb+qFUBl09vXjhmwvQvL5400XlWD37\nP2YaqCZiITzwbOnO3sbzDo9lC/ZP3lxzE3NPjXUuq72KUvd8nHwOXuy3VWLfTjknJKg1egqlNJQs\npZ7wJ287qxFz01i0VOw2JqU9LYLQYLYKCIV4JGJhPL5kLkZtPu0pKyMzA1VRdOfsXey82lSmgllz\nRuO5rPZNrH7n9V6DV/ttldi3K2pe7DKV5XblqDiq6FbeC660lqJXYEVj18zYzt5iEKCgRZQNs4mu\nJhxCIhbGT945UZBuYU0eSjrHzEA1HpO7B//hB3dg76ob0f0Xf459q78MQH46FgTRscQeYP/xmzVn\nNAu0rOBj9btq2muwwks5tdcTv9sJ2837Kp1aLWZEXQ2NJEmIQZQdVmqpMRHF/TfMRG2Ex/bONtmm\nJy2AZzxWKZMWy0C1a2ETkukcrmiIq+ma5dfPwM7fnsS2X/aja2FTgYOCkqYs5m7AEjoovnjGvllm\ngVaLnZ5PfvkOeoHxc6wN88wyBa9TT05NaO3g1p/Q6fv8ctII2jn9hPa0iLJixzyV1TU3EQujJl+M\nWhPikcrKk/bwWA7P/eZD04C0YWkLXjp0GouvuRSLt7wlr7z2fOB6P8StV6HVvglg3l3XjnlwJWAq\nLpe3qg8H2nFadRZ2G3iDaFdVjQTsPto6MQUtoqwU2/Q2+/3jS+Zi0eZfMQPT1o5WeXLMCMxCU0Wi\n/tnvvow//OAOW2IPwP5Kwg5WwRqAbRf0AEwsAOwZu6qBNxoqu/ggKATxs1MIiPhCS8UNcwmigGJp\nMrPfX9EQR06UsPiaS1WvOQCqPH17Zxvi0UKhhLL31T8wAgCmPZmM6TYnKwk7f+DFUjRWv/OjtUap\n2DF2rXSKs9IBI4BBQYfb+rRKQ0IMoqwU68wKAPtWfxnt86brfq8EHavutUpAMh47mc5h7/tnEOY5\n7H3/DLYuby0uumDVbu2UW767VfFZbXTbNcQNijec2eeofE7Kv5VgUW7xQSk+i17d56C7TFSryCe4\n4ZQYl5h1ADZ2Zt24rEVtsrhxWQv+7tU+AOYrJSUwsboTxyMh3H/DTHz7K7PUNF9R0YWDlYQVXtZF\nBempnfU5KivRMM/pxBGVEAK4XUV4eZ+DHhSCLPKxgva0iLJjnMh5Duxi4E5ZpKANaFbqv6FUFj37\nP8biay7FrKl1qlOG1orJLk72bMyKiBX7nJUGZaGbCdArs1sv8XLPz/OxuSzi9fI+B/Ez0xK0ByGQ\nEIOCVrVQbIJxIq32Kli43dPSvk9xmmc5kyudd+1O7JVwUqhm3AYML+9zAINCAZXe9zNAQgzCO/z8\nchdLU7CECHUhXvdv4GJTvmQmh8ZEDN3tc/DuHz7F5z97CRoSUSQdtLxnpbRqw7wuzci6B9q0lGnx\nczSM2Y++4mgS8yOVE7AJy1Pc1nJ5eZ+roT4qiCKfYtBKiyiKX0+MoihhLCd3e43Hwjg5mMKWfcdw\n9kLa1fG9Vvy5uibNk7pZTZidFKOdayvVg9B4vB/ddR1CPO/aLT1ouAnK1bA6GsdQepDwBj9y86Io\nYXgsi+F0DrsPnlZNR5PpHKIhDtFwYdPHogW8YzmmkaqbIOEW7b1itVrZsLQFm17rw57DnwBwlnoq\ndWWkfX8yncMz73yIzfuOA5BbfXzntmY88qK9tjDjmfG8AnVKme8FpQcJb/BDBZXKCjifymJP7x8L\nnNq3drTikvDFY9vt9mpmpOpU8VcK2rTUy0fPoGlKAk/e3Ya6mrAaKJSABVinnlgThttUDuseblja\ngv5zSew5/AkevrkJj7x4pCI1O5UOEl7e5/FEUFedVKdFFMWOQamd2hbtayDJDuksp/aVPb36Xj9F\n6l1EUUIyk8PJQbZ5Lat2yC+MJqpKmwqe45CIhtGx4Epb9Uql1BmxYN3DtbuO4OGbmwCY17/5Lc/2\n+jqr7fxBJqh1ZhS0JhhuCietikNFUUIqk8NgMm35h18wOew4gJF0ztZkabXSU44bj4axZd+xApf4\nrctb1cLichS1AqW3lge8nzCs6s7CPGfbrd5rKj0xVvr8QSaodWYTd+07AXG73DdTQQGyZ14yndM1\nQmSlllJZoaBV/W/6z+GLTVOKqrWsFF0AVHn52QtpbHqtTz3HqaEUJtWEiyr+yoldtVaxQO00nWZ+\nD3M49v3bMZYVbLnVe02lJ8ZKnz/IpDICuhY2FTS5rHTxMa20JhClPFWyVg/K8ew0QmS1qp8z/TOI\nR0LY2qG3Vdra0Yra8MWvptVKT5l0nnijHxuWtuDccBpf3fY27vrxfiRiYUTDoZJ7BFXCPsnK7spN\nOsvsHiai8r2JR8NoTMRMV4F+3YNKt3mv9PmDTG2Yx/LrZ+j+ZpdfP0P3t1kJSD04gfC6QFU53i+6\nbija7oPVqn71olm470tXozbfckTxD9z7/hl0LLiyYNJkrS4Utd6U+hgeWdyMyybXyn24OKDGg1WV\ndnU6bVIMqxbNxozGOFJpeSy+SedNVsWJWIjtHmJTNu9G8ODnhnylN/srff4gUwFHD1IPEnq8LlBV\njqescrQKQGNqydiqvn3edNx57eVYseMg0zni3RNDuj8Os7RaPBLCj+66DsPpnEGu3YqaIqktO5O4\nspqcUh/D6luaC67Rr8nNNCXLmTeMtHPMulj44iqJkyemYsHLTzfwShfgVvr8QSaoqVNKD04g3Lht\nW6WFlOOdG05j8+t9eHzJXDm11FkoMDCmYR6+uUlVDZaiXON5DiGeV+XaF9OevZZpT7uqMeUPVzve\ncm3YM1OyJaaz3Kjl/J68Kt3mvdLnDypBTZ1S0JpAOFGvAcUnOO3xNn+9FZfUxwAJqKsp/MM3Bkxt\noDJrKWL3j8OsPstqUrW7v6f84fopCXeyX1Rqmw83+5pBnbwIf6lESxk7UHpwguHEa8xOWsju8Yxp\nmGQ6p6Yq3/3Dp/jRXXIBrnZPy/ZE7CLtaXf1oPzhKpJwr9s4OLVTYt3HeDQkpzltpLXcrJrc+vgp\n10fuEtVJUFOnFLQIU0pJC5lNVsoEH+I5bFzWgt0HT2Phn07Dt144qHPEaIhHbP9xuJlU7QY65Q83\nEQv5Igk3PhhMqY8x9uf0e2eKMfDgiHMBgZsA73byIpFD9RNEQ11SDxKmuG7vYNN2aXgsCwnAX73w\nXskKJadP9HYnVO1xx7ICRBGuDWVZYwQHnaLTzGT36XvnQ5RQvAdZGZscFiPo/aSIwEHqQaI0XLd3\nsJlWrK+JlKSG01LsiZAVMIqtHswm+Hg05HjStZKwa1c+rL2zaZNiSKZzhlVeK6ZNiuleZ+e+lTPl\nE1T1GVHdkBCDMMWpcEPB7mTlhRrODmaCEgCWqjEvLX7MjiWK0G12s+yUVi2aja6e3gJ15KpFs3Wv\ns3vfyqWWIwEH4QcUtAhL3ExwTiYrtwolRXEniCKGx7KWyju3wcfLlYLpsWIh3YPB1EkxbDM4hMxo\nZDuOzGiMB07ZpSWo6jOiuqH0IOE5TtKKbtJVysqpZ//HBW1NWPszboOPl8XYxY6lHC8eDaMmHNLd\nj1Ta5L1pIXDKLi1BVZ8R1Q0JMQhfYIoOAE/kz8oGP8tJg7XR71YQIAgikgZ7qeULZqAxHkUo5CxJ\nUYoAglR4xASBhBhE5TAKI7yceJWVk92CX6uVn5nqUBQlDKWyuvdsWd6Kgx8NYf5VjY7HXeqqozYS\nwk8fXCD7KvJATdj7FUs5a6qofotwC+1pEWXBU1FDPtVm10nDTFACwNTxgzXeVTt7MXNKvetxK/VV\nqYygFgQXc0tXRSQ7LvYhS6a9FzKUsxkiNV4kSoGCFlEWPBU15FdOe98/U9D00WrvzKy1CiuQWjVN\ndDtuN5N1uZoUlrMZIjVeJEqBghZRFhQxgRa38mdl5XT/DTNx2eQabO9scyTJV7AKpGYKSGV152bc\nbibrctU6+XUelq8i1W8RpUBBi/AdUZQgiCI2LjOuilpdy5+VlVOI51FfE3FVc2QlzWfJtTcsbcHe\n989gW8e1qA3zjpsiupmsy1Xr5Md5zFaWY1mq3yLcQ+pBwje0m+0nB1N4s28An//sJWiaWodTQylM\nnRRDPFo5LVAxcYggiEhlZfVgMp1DbSSEsZyI2jBfINKwIypxo2Isl3LQj/OYXm/nfIzmV52khiQ0\n2PrwKWgRvsCaBDcsbcGm1/qw5/AnJXVM9nqcZupBs0k8lRV882Rkjak2zGM0J/qutPNa0WfVKRuS\nN+UPxLjC1heA0oOEKdr9iOGxLARRtJ0KY+3frN11BA/f3ATAOh3kpL9UqZg5frgRabDSfNprSWUF\nNMQjlrZYrJTaUCorT+o+2y55be9klXKkxouEWyhoEUyMk+eKHQfxx/Nj+MnbJ2zJk63Ud1Yqv6DI\nod2INIxB2GkAEkUJyUwukMo6Nw8SZONE+AEFLYKJ2Upp8TWX2ppEzSb20YyA7Z1tBW1KlAkxKJO2\nU5EGazJ2ohZUAlw8Gg6css7tg4Rbw2WCsIKCFsGk1DoleWJvLVDfrX/pKBKaFYZxQgzKpG0VmOxO\nxmb3sDZSqDxUApzdgulyplBLqauiNCDhNWTjRDAxM3jV1ilZiQ54nkMiFsbjS+biioY4+gdGsOm1\nPpwbTuvea+y9pRzf67b2Tilmu2Sno+tYVsC+1V9Wr/+JN/rRNCWBwWQGKw0dkBsSEfzuoyE88UY/\nNixtKTAB1q7iyu1FSHVVRJCgoEUwYfn1bVjagpcOnba9L1ETDiERC+OuH+83nYCNE6KdSbtclNJq\nXBQlJNM5rNt9VL2OjctaMKkmgoeeP1jQIHN7Zxs+d1UD9hz+BADQ3T4HTVPrkMrkkIjqVyh2mmx6\niZdu9wRRKiR5J0zRSqCT6Rzi0RBGs6IjeXIxGTWrlmf1olm470tXIxELV60c2qxG6acPLvj/27v/\nKCnKM1/g36d/TM/0zLgRBBcVRB0ku8gwKgdW82PFVRFzzuiBS+LsJYSbrCasrnqJRpN4784mZgkL\n8QL3eJKgyUmQLESPXnd2gyGa6NWzNyEgP8VddGIU5sLChDFhZnqmZ7r73T+6u+gfVdVV3V3VVT3f\nzzkemZ6e6rdqpuvp932f93kN08DPDJn3nnKv5Tun0j23bJBzcgkBq8yTS1jlnSqT29NobQwDAFoi\n9qZBS/VW9Hp0XQsvTfcuRHz7Sd5oSM1sbyyzSu5G694AoOfgCUd7PtwXi7zEn3cEqhv1ekM0GlIL\nBKCzTUoHkqkUvrBtX15PpjF0bkhUb0jw4ecOobtzDvoH444PoVYyVEpUTRweJHKA2ZAakF8NIiDA\n535gXmHDrLpEvQR6mvA4PEje2mzPS21xg9lwXzYYRcNBQFAyO4/JEERpXKdVx7xSXaIWbSlcx5RM\nplxb12R148bs846diZVcm8XqEkRpHB6sY+VUFS9UqneU+/3RzE680UioqHdRaVvs9NIKh+b+d1cH\nPtI2Bc2REHpPD2HXmyfRtfBSx7LfrJ5r9nlTWiN48JbZRWn+pQrput1TrfXrU93j8OBEV+mi0FKp\nzrnfv/C8CL5064fxxWcO5q1Lao2E0NoYrqgtdlOuc5MWOuddhGsunYTPP/1GXtbd9t3v47MfvRwt\njdbfAlZv2lbPNfu87DxVdm3WyFj6NQqPXctkCL3fwaauDkyONiAY5IANuYd/bXWs0o39jMr3DI/l\nlx765btnsPqGNnzxmYN5z33o2UP4IDaO2HiyorbYLSOUGzTuWdSGB3Yc0K2hGI0ELQ8T2hneHI4n\ndM91OJ7IP6+ca9Jz8AQWb3wNK57aDQg814PR+x3cv/0AhseSjgy1ulmmivyFQctFbr8RK50HMe4x\nhHBmeAxN4YD2/WxNwsLnTp8URbQhWFFb7PbScoOBUbvaprbg2JmY5UK8dgJntCGIdcvai+ouFvW0\nfDRPZfQ7aI6Eql7M2EtzseQ9DFouqcUbsdIq20a9o97TQ+kbds73jQq9Hh+IafsnldsWu7203GBg\n1K6h0QQ2vvy25aFSO4FzZDyFF/b3obtzDo4+tgTdnXPwwv4+jIyn8p7npyroZn8L1a5BWEmBXqp/\nDFouceONqNeTK6yyDcByb0+vJ7BuWTueeKVX+5Sd/f63X+3Ftz45L++565e34/xoWOs5lFvxuykU\nwHc/fS1+8/e3YdcDH8eam2aZ9khyg0Hb1GZsKqg2v/HODvyf/X04dTZufajURuCMhoPoWngpJzsR\ngwAAG2hJREFUunuOYPajL6K75wi6Fl6q216/VEGPhoNF13HdsnbsevOk5Wto+bVYoJdMMHvQJWaL\nQ6tRL85KskI5NeSyGxNGG0JapfKegye0bLhoOGgpe9Cs3aWyEytNAEilVPrYkSCOnYlh48tv49TZ\nuOG567UJgK1rV4+ZdslkCsNjScezMKuR9Uq+ZOmPiEHLJU6/Ea0cv9w2OFUw1cpxzdqcGzCtBAYr\ngcROJYt6CER2uRGMWaB3wmLQ8pJqvRGNbhpWenKV9PacuFlZCaJmbS5VFd2pNpHz6rGnSiVZ+gVz\nTssl1Zh0N0vmsDLnUknaeaVzL3rzbVbmLrJV0QvbPBxPODJHaNYmZq+5xy9zfeQ+Bi0XVfpGNEvm\nsJI+XUmKdSXp+kbBNmawnik3iAYCwPrl7UUJHk5M1mc3btRr07EzMaZdE3kAxzt8xOxGHZDSW3yU\nuw1IpUObettqbN/9PlZePxPrl7fjoWdzyxd15AXRxnAQG3Yd1apF9J4ewoZdR/HYHXOrWkA2e47b\nd79ftHPyumXt2PCzo+gfjFe1BBYR2ceg5SOlKn1bKfNTTimgSrd31wu2i6+ahtXb9mFKa0QLSMcH\nYmjOnEf2hg8FnDobx+KNr2k/e93lkw32pUr3Gs12XM6eT2EgyT3H3v5hPLlyPpoagukg+bOj6Dl4\nAqGAVK0EFhGVh0HLR/R2+XWjgkI5Q3GFgeO+G9vw+MvvaN/PVqpIpFTRlvGFNQ2Le2PpDRIbQ0E8\nuXI+opGglmKvlMJAbLxoh98X9vfhM9fPxFgyhfu2HygKJLnn2HPwBO5Z1IbuniNl9+QqDfREpI/v\nHh+p1S6/dvdy0l1bdWcHAGDzL3q1RAqjYwLIu+GnFLB26VzMmBzNz5hMKYyMJ3HX1r3a63z309ca\n7vD7QWwcX37+sG4gyb5+9ntPvNKrO3QZkHRGY6lrXyrQc+iQqDxMeaeS7A51GaWNb1l5bbpW3VgS\nTaFAUY9IWw8lsJSaPxRP4Puvv4vFV01D29QWnPj9CCY3NyASDuYthA4FBEcfWwIAmP2o/nGhihcP\nf2fFNQgGAlpPLplK4Qvb9lV0DbLryzh0SFSktluTiMh0AFsB/DGAFIAtSqlNIjIJwI8BzATwHoBP\nKqU+EBEBsAnAbQBiAFYppfZljvUZAI9mDv2YUuqHTrWbitnt4ZkWVx0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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5012510790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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CKOKDKK9RCr5/eQSXBnnTScJM0eZkgkndJ61H4kN7juJyLJF6ys9TQed00nNT\n3ViKjPfrJ+xDk1aJY/SEP70mnLXNsoRcZ4Bft/co2j93JX6wrxffePZN00FF/fSs1/tq3d6jiCdF\nbFrWmNUGRD1JREI+7GxPtyppH20g6WSCMbtPsiLSasNK3f07nPTGuxHteL9+wj4kEypxjFRiZwZi\nmtfZMTcNB32YMiGE/Q/epCj7Hnu1D9UVAXQfOQc/x0wHFfXTs1Hvq7pPVuJbP+/Bzvb5qAz60Hdx\nSKMM1BMRyMe0o1S0cp8+VR1Swmd2FXTqfExlwIcn752PioD13EypGtG6lYcq1esnigettEoco46/\nE8MBx6GukYSAtYsa0Nl9fDQ8uKgBf/loGMCooa9RiFD99KxuKSIj97668DGP9z8cxme+8wI6u4+n\nVIOwFjKym69J3admzT3ZtKwRE8MBx0W0WfmYrkOI8gIgwXIOqRQLe93MQ5Xi9RPFhdSDZYDb6sGh\nkaS+3Ly9BR8MxREJ+rDrjdOGhrhqJV1rUx3W3t6gkbbLhrpLW6Zh8/5eXPiY19ZgFcgLTxZcyIXS\navWgE9wy0C019ZzbxsGldv1EwaDi4vFMPsWi4ZB+nqEy6MfDzx3G5mVN6LsUNexcq25jodf7Khz0\n4b4bZoLjgC1fac4aqHKFjJwOchzHUFWRej8YbIXxdO9THorBzPMvpcJet/NQVNhM2KGg4UHG2CcZ\nY79gjP0fxtifGGPXM8ZqGGO/ZoydSP9/Yvq1jDG2nTHWxxg7yhi7RrWfe9KvP8EYu6eQ51xqFEIy\nbKSE67s4hNdP9mPtniN44JZ6w4EqU9Rw340zlVBedUUAPo5DVYUfFX6fImGPJQTlnDNDRh0LZ+GJ\nu1uUflb5yPndvF9OFIPlIPEmg12imBQ6p7UNwD5Jkj4LoAnAnwD8LYB/lSRpFoB/Tf8MAIsBzEr/\ntwrAYwDAGKsB8L8ALABwHYD/JU90RGEkw3p5BnU7e7kzsdlAlSvnZDZ4qye93g13YPmCGbj/mcNK\n3miQT2JSdcjR9Tq5X+o6syFVLs9JPqYcJN6UhyKKScHW4oyxCQBuAnAvAEiSFAcQZ4x9CcDN6Zc9\nDeBVAOsAfAlAl5RKsv0hvUqbmn7tryVJGkjv99cA7gCwq1DnXkoUQjKcqc473R/D5pd6lZYjsuou\nn4FKPXgDwOsn+7Hr4Hv46g1XIRLyK7VTsYSgSObl1z205yg6W+dYaoGSid37lcsOya6KcSwk3oXO\nETm5boLDF8rWAAAgAElEQVRwi0KutGYCuATgJ4yxtxhjP2KMRQBMkSTpPACk/z85/forAJxRvf9s\nepvRdgKFC9UoeQYJiIT8uDTIa9SJkyeE8vKxyxy8W5vqsGTeNKzqOqxZeVUGON1Bvn5ylfKzneu1\ne79yrYzsqhgLHVobq/BjKbhtEOVJISctP4BrADwmSdI8AFGMhgL10PvWSybbtW9mbBVj7BBj7NCl\nS5ecnG9JUuhQjX7RbQjhYH4DVebg/cAt9Vi392j25GAwyJ8ZiDm6Xiv3Sx0OdHtlpHf8bW3NqAxw\nmtCjUwoRfjQKjxJEMSikVOcsgLOSJB1M//wLpCatC4yxqZIknU+H/y6qXj9d9f5pAM6lt9+csf3V\nzINJkrQDwA4gJXl37zK8TTFDNU7CUPJ7KgMctrU1Y0269YhREXIk5FeUiOr2KJGQXzHPtXO9ue5X\nZjjwQMcXXC1+zTz+0EgST/3+FLa/3OeKE7vbkyy5xRNeo2ArLUmS/gLgDGOsIb3piwD+HUA3AFkB\neA+AX6b/3Q2gPa0i/M8APkqHD/cDuJ0xNjEtwLg9vY1IU8hQjVG4SRBE22Eo9b4a1u/D7oOn8cTd\nLenJJ2kYNjNc6Tm8XrP7FUsI2HXwPXS2zkHvhsUI+Bh++OUmV1ey8vFjcQH3P3MYWw6ccG1VZLeD\ndK4VVDkIR4jyoqDFxYyxZgA/AhAEcBLAV5GaKH8OYAaA0wCWSZI0wBhjAP4FKZFFDMBXJUk6lN7P\nfQC+k97t9yRJ+onZccdbcXEhMSok3dHeglVdxq1F7OzLbo+sQiKIIt6/PKIpht6+vBmVQR/C6YnG\nzsrObDVaiO7CVldGll9XoEJvgtCh+MXFkiT1AJiv86sv6rxWAvCAwX5+DODH7p6dd/GSQ4BRuCkS\nMm8tYmdf4aAPHHMnzJnvvYvFBSW3BqTUiqt392BHe4uyMrNzLmYTgx3fPTudla3cRz31pl6xOHkD\nEl6DvAc9hteKT43CTVHeOJxnd1/ye/INc7px74wm44iDAVqeGCZVh/Cr1Tfi2a8vQJRPYiSZu/2K\n0b6shOms3EeruS+qySK8Bk1aHsNrOQSjQuPfnbiEbcubbQ1mhR4A3bh3bkrSZbf8tbePmg8//Nwx\nxWzYTjsUtwUWVq8z35YtBOE2ZJjrMbyYQxBFCdF4EuGgH30Xh/DoK33oPnIOHQtnjRYD21QPZoau\n3AiJunHv3FTLDfFJfDDI4+HnjuVtLuu2Sa0giOiPxRX1JqkCCQ9Q/JwWYR8v5hA4jiES8mdNCNtf\n7sN//+Is3VyP0SSkZ47q1kThxr1zs4QgHPBhRm3YlRWS2oRY02PMwSpVFCUMxBLYffA0OlvnoH5y\nVcrI2OF1eikHS5Q/FB70GF7NIdiVUtvJLWWG9SZVhxDlkwBDlhRbLdMeHElAEEXlNW7dO7dKCDiO\nIca7E250K0wnr5pX73oLWw6cwKKtr+Ez33kB9z9zWGNabGd/XsrBEuUPhQc9QOaTaqWfw3BS9NST\nq53VkN1Qljqsp9d/Sz4OgKxzkHtzyb29AOd9xAqBl4pz5XOpiQTRsD47jNq7YTGGE/ZW9G6HLYlx\njaU/CFppFRm9J9WBWCI12Fp80h8Lm51CigbUqzhDO6eEoCu0WLf3KBZdPVV5jdc88XLdt7G0SJLv\nn1k3adthyzEwACYINTRpFZl8FW9jGZ4xmxDUg2+UT2L1rfWa95qFxNRhPSM7p3DQZzhA1k+uwpQJ\nIUCCJ/3xjO7bWIfW5Pv36Ct92Jqh/Nx4VyP2v33edtiSemsRYw1NWkUm3ydVp5Oem0/4mYPvqq7D\nWH7dDHQsnGUpt6RejQybDIJGA+RfPhrG2kUNWNlVWnmVsS5vkO9f95FzePHYeTy+ogW9Gxajs3WO\nEmK1m/8rdA6WzHqJTCinVWTyzQk4kXm7nWcxs3qyI4c3OrfHV1wDH8ehMsihP6qVaW+8qxEBH0PH\nz4+MWV7FLbXcWJc3ZN7b1bfW497PX4WqCvv2VJn7LUQe0e3vKakcPQ9J3kuBfKXMTmTeVi18LF+D\nidWTXeujTMn5SEJIhRuffVMZaJ+4uwWRoA/RuJAacHkhFR7MOH446FOKeN3CzYF0rMsbDOX8Nj8j\nvf1mljG4gZvfUy8JYoj8oPBgkdFL1NeEAyn5sYWQiJPwTLHcFayizgGJErA63bk4KUrYcuAEnvr9\nKfTH4rj/mXTDyK5DWLuoAa1NdZrjn+6P4YMoD0EQHZ2HHm6G9IpR3uA1oYoZbn5PveY0QziHVloe\nQP2katft3EkxrNtP+G4WvmbtW2fgWnT1VKxJT2RA6gn8oT1H8cjSuXjh2HklbLj5pV5cGuTxxN0t\nqAoxXUd0u+EiqwOplX0Xu22918Nlbn5PSeVYPtBKy2M4eSK0+/Ts9hN+vqtFM/SKc40UhjNqw4qw\nYPNLveg+cg5TJoRS+aGMQmWnyj0rq0o7+x7LlY9a1BCLJ9Ef5T1dFOzm95RUjuUDCTE8xlgl5wv5\nlG0nf2Dab0pMuV7wSRFrdveohBkt+Maz2b28Mnt8tTbV4dt3NOChPdmFyrGE4EgAY+XavFhwq9eR\n2Q1PxELjmuiFclqlgKUPgiatMcDOH57VAc+roR0jc12jazAbSOR7sWjOFPxf86ahqiK1z5OXBtHy\n6RrNRLa9bR5qwgGNCazZwBwO+hw/HOS69140Pc78Xv35+3fqumKUc3NHr/7NEAqkHvQCdp/wrOSH\nvPrUqHdeG+9qBAC8cOx8Vv4glzpMzkO8frIfb57+EA/cUo/6yVW44pOVqAxwurmg2nAwpS4M+cEY\nDPMY+eRLcqnlvGh6nJnTkV0xvHSOhaZQKken0CTqDMppFRi7OSordkluKaHcLtw0sll64JZ63fxB\nruS4Og/RfeQcFm19DSt+dBBgADNYDfh8HKpCfgwnBFOz2kIq97xoepzZtPPRV/qwaVmjp85xPEFG\nw86h8GCBKUSoqJh9o0xzUAbn1bthMQai8ax95wqF6p9jM6pDfgzySazO0Qsq1zUWOq/npadoQRTx\n/uURrRHx8mZUBn0I2ywAJ/LHi3lPD0CGuV6gEKolu/vUW1FZWa1lvk8QRNOnQ+PzSupOhpV+Lqv7\n8bblzaj0j34tKwM+/HTlAvR893ZsXd6M7/3qT/jLx7ymdstopZlr1VqsmiW9z6PQdkXDCRHPv3UW\nna1zFIXlrjdOA4wVvWZrPFo1kQTfOTRpFZhChIrs7NMoDJHrj0b3fbE4dh18z3CyMDqvSFB/QBxO\nitj9xmnNQLr7jdMYToqjx5f9BLsOgU+IECVgeo31xop2JyY3BlCz0I/+73gMjiQKGioKB3xoW/Bp\ndHYfR8P6F9HZfdyR16DbjNcwGUnwnUPhwTGgEKEiq/s0CkM8ec98XBzkMb0mrKj8Lg3ySnjC6H2d\nrXOwaOtryrbMsKSdazULc8bi+pL0ztY5AIDO7uOmYUUn91sdTpwyIYQHF87GjNowYnxqX1bDplE+\niZ/87hT6LkUV8ciZgRgmTwhBlKB7XY8snYubN7+qez1u4bWQJTB+w2ReFVMVGVIPeoVCqJas7lNv\nRTVlQgjReBIPP3dM+YPZtKwR1SG/8uRt1gZETabizM61mqnszI7/P3/Wg03LGrPqr8IBX16DgRwy\nnVQdQsdt+o0o9fahe8zlzYgLEtbuOaLJx9VEgrrXNb0mnLVN9k50a6LxmnoOGL9hsmK7oZQyFB4s\nc/TCEA8unJ2VE3poz1H4OE75ozEKX0T5JDoWzsL+B2/Cn79/J564u0WTg7KDWZjT6Ph9F4dwaZBH\ndciPne3Zuap8lJXyAGrWiFIPvWNG4wLW7jmSsY8ew+s6MxDTbFt9az2ifBJgwAeDPDp+1lOWobPx\nHCYrJR9IL0GTlkcoVDJab2KYUWuQEwr5lOOaTSjLF8xQciP3P3MYA7GEo/M1E0roHX9bWzPqJ0ew\no70FVSE/qiqy/+CdPrmLooShkZQs3KwRpR56xzTKu0VCfp372oyJ4YCyrWPhLCy/bgZWdaUMgR9+\n7hg6bmvApOpQ2Zm8erE8gPA23ogRjHMKGd/WC0PI9UuZYbnT/TFEQn7luHrhi1hCyDKrzaetiVHI\nKvP4QyNJPPX7U9j+cp/p/TEKOUb5pGlvr1hCwFO/P4WNdzXizEDMVuGt3jHN9qF3XwEo26J8UmNH\nJde7dbbOwV9t/21Zhc4oTEbYhVZaHqDQbRMywxDhYOrpVh3me3xFC17tvag5rl74YixzEPLxY3EB\n9z9zGFsOnMh5f3RXaMub8ZPfnTJVp4WDPmx/uQ+bX+pFwMewva05azVk9PSvd8yqCh82L2vSXUHk\nCgtFQn7DfJ488ZWTTJzCZIQdaKVVQKwm0cc6Gc1xDDXhAJYvmJHVBbjnzIca2bty/rwAjgNEEbbt\nf9T7GUkIEEUgHMqvHciUCSFASikQNftMCKgJBzSrlp/87hS2HDgBwHhlqG5F333kHFqb6vDI0rmY\nURtWVqBG55m5WjjdH8M//L9/AgB0ts5B/eQqxOJJQ+m/npmt3j0+MxDD9rZ5qPRzpDwjxi200ioQ\n6vqTjp/14INBPtUeYyT7qbgYyejhpKiE+dSWSw8unK08yWvqZ7oOYSAax943z9iy/8m8DwPq2iuH\n7UBam+qwdlEDVnbp73MglkgN7ENxhIN+bH+5T7M/vQeCzNXSpUEeHGP4l389gUjIjwq/+QOEOsy5\ncMtvlMlv0dbX0LD+xVRo0qBVS+ZKe8uv39G5x82YPCGE2kgQw0mRGhoS4xZaaRUIO/JpN5oo2pVG\nq1cvrU11Sj3RcFxApZ9DLCFg18H3lJVC38UhPHf4LBZdPRU/2NerrEJyHUs9IO9/8CY8tOeo7XxY\n5v3puG22sh+jfe5ob8HqXW+hs3WOpZVh5mopyicRDvpw340zbeVYjHJqQyNJ3P/MYd3vQOZKsvvI\nOXAM2Nk+X3dFOl5l4gQB0EqrYNiRT1sxyTXDiauAPLi2NtVh7e0NihpwZVdqpVLh57Bk3jSNg8KS\nedPwmUkRdB85h4VbfgMAOXMQ6gHWrirP6P6o1Y9G+5TzQo++0oeNdzVm5bj0ZPrq3Ep1RQA+jrOd\nYzFSPT71+1OG3wG9lfaFj1Mrc708T66VeT75rnLKlRHlCU1aBUIeWMwGavWgkE8y2omQQx5cO26b\nrTupDieErO3r9h7FEJ8EYH2QVA+wcjsMNVbDoOr7Y2Wfsqt595Fz2PxSr2IV9diKaxSrKKeYXa/R\nA4hZiNKu7Nvs9fnYIum994MoD0Fwfq8Iwm1o0rKAk6dPeWCRpc9qrr2yBicuDLlWLOokXCQPrkY1\nW0YKtuqKgK1BUj3APvaqfjuMSj9n6/7m2ue2tNJPfs0Lx86js/s43r88jO/+8ji2v9xnK5Sm+fxH\nklk+gR9EecRU5w9A8wAynBBNJ2u7K22z1+ejRNV775pdPYimc5wE4QXIezAH+dRQiaKEkaSAaEYb\njY13NWLzS72GHX3tko9/m9F7M1vXK/tsnw8wKDkWK8c2Uw/KE9blWALTa8I4MxDDxHAA1RWB3F5/\ncQGVQR/+8tEwRAmo+2Ql+i4OoX5yBD6Os9VF2ew4mZ//pmWN+MG+1OcnX+8jS+di4Zbf6H4/xtJn\nLlfbGqetZYYT5dsckvAM1JrEDfJ5ck0l2f2ojYSUp+LO1jnKhAW4k0DPx1XA7L2624M+2w4U6tBe\nOKh1suAFEYN8ygexYX3K/WGQT2IkaX5/OY4BDFjxo4P4/MZXcOMPXsFnvvMCOruPYzghKq+JBP0Y\niMbR2X0cLxw7n9MR30oLl4f2pBpbqq93ek24YDlLO5jlu3Ktis2ss0jkQXgFenTKgRtKLXnQHuKT\nWe7kbrQ4z8dVwOy9RtvlFaQojl5D1jXxQmpFluN8RBFZ6r+H9hxNrehyYEV1afXeGK6GqvQNbtXG\nwddeWYNzHw5rfp/5/Rgrs1qze6KegIFs9WY44MO2tuas2r3n3zqLKybOLMh5e9F5nvA2NGnlwMyJ\n3O4fsRvSdiPyGRTNrJQyt4uihMGRBAb5JB7acxRTJoR0HNebIYgivvHsmznDYeGQwUNBKPc90ZuQ\nZLl+5iCY694YDeg72lsMC339HFPChSEfh9amOnQfOefKg4gZZgO92SSd6wGM4xhqw0E8cXcLIqFU\nSPX5t84WrO8WtecgnECTVg7cnGjKwWctlhBwOZbAw88dUwZyUYKmbotjwNeeGs1zTaoOIconUVsV\nxBCf1FyzkQ9ijBdQVZH766mekMIBH/qjqUaVi66eivrJVRjikwj6GIIB564kmZ//trZmSBLQu2Ex\n+i4O4Qf7enFpkEdn6xxcGuQLavhqZaA3mqTVD2Dq2rwoP+rW4fNxqAqlBB2zplThion26tTskGvl\nRxB6kBDDAhTCGEWUJEgS0LDeJNmvSujLdWBGxdWpQZjXCFW2tzWjNhICgKz7DkAJTYZDPozEBYhS\n6t9RPonfnbiEOXWf1BxvW1szEkkRew+nVg16T/JDI0ms7NIRlLSnHzBU51EZ4NCwfp9h88pCfj/y\nEd3IE96ug+9hybxplvuFFYpcohFi3EFCDLcYr4aeusKEuKDI+Fub6hTD3QMdX8CITrFsruLq1Ooz\nlCFSSE1YejVDIwlBsW3q+FkPBmKjFk6rug7jmk/X4Pm3zmbJthOChCXzpmHXwfd0RTQchyzp/KZl\njeC47M/fTMJe6O9HPjlWeaX/1RuustUvrFCM515ahHNo0iJ0MVKaVfo5TAwH8M9/04xv3zHqpPHw\nc8cQTU9sauWhFRcMvYcCo5ohQZIU4cY3b65X/i2/5sHdPVh09dSs402vCWPd3qNYdPVUjSGwPCmL\nIvCvf7qgFCF3ts7B5v29qAj4siZuK2rNzNquWNwdl4l8B3qOY4Y1eGOtEKReWoQTKHA8TjEKeaq3\nR/kkJlWHNE/jO++Zj+qKAKLxJP7H/5PZV6sHT947H6IE1FYFsaO9BXxCwOpb65UcU9/FIex/+3xO\noYLRikI94BpNiGplHzAq25Z/J1+vlforI89Ao55YQ3wSlYGUC7tahbdpWSM27+/FhY/5vEJxRjlW\nud7NSgjbTXFRPpRDjpcYe2ilNQ4xWkUJgqjZ/vBzx7D29ga0NtUBGH0aN3panzIhJbiQ37+q6zCG\n4knc87krNR6Gy6+boev9p0YWaKi59soaDA4nLVk4qZ/eN97ViEdf6VN+lyn/Vtdfddw2W9cz8M65\nU9HZOgc1kSCi8WzXC2A0nNl3MZrloP/QnqP41u0NeYfi9Gq+asIBDMQSlq2bvLTCGa+hd8I5NGmV\nIblsp/QGbDnXk7l93d7RQlp1GEovTPXgwtlYnTFYr9nVg8uxhHbb7h6lANjo/Dmmn2NKioJigGtk\nCxUJ+rCzPTWoP7J0Lrb8OqXu29bWjEjQXP49ozac5RmYaSq8qutw1qSgvndGK8ArJlaitaku71Bc\nVo7NZquSsSx2Jgi3ofBgmWFFEp05YLc21WHJvGkIB4075mY+jVf4OE09z/63zxv6GE6vCWdtC4dS\nvoVGRb41kSA27+9VWqMMjiRQFfJjJCHijVMXsaM9deyRuKDbwqPKl7Jx+lR1CFu+0pwVesoVIpOL\nwa+9skYjJgGypdmiKAES8OzXF6Dv4hD+8tGw7r5P98fwwC31uDTIW5b0W8Gp9+RYFDsThNvQSqtM\nkFdXsXhu2yn1Kqm1qQ7/8KU5uGJiJQZHElh9a71mv9deWYPhuKB5Gk8mRcQSgmbCWr5gBkYMRAJn\nBmJZ2073xxCLC4YNEfsuDuHCxzwefaUP718exjeffROf/ft9WNl1CC2frklNQIwhHNLaQgFQVpmx\nhKC8LjP0VOnnsG15s2nLEjmMZiYmUUKtXYeU8GfAx+HxFddkhSi3HngH9ZOrsGlZIwRRdM2EllR4\nxHiCJq0yQJ2jqrTw1K20JVk4C2tvb8A3n30TDetfxDeffRPLr5uBjoWzNB1z1X6DoihhYDiO+585\nrOmztfvgaQiSlJUr2bysCZGgT3cAD4d8qEyr8+T2F5UBDp2tc/CZSRFsXd6s2zplze4e3dYidtpy\nDCdF7H7jtEYtmNmyRA6jxeJJw0lBV+W4uwccx/DI0rmjSsSXUiKMwZEEfrCvF9949k3XJOZeylER\nRKGhuEAZoB44ZXGCmTJMXa+jdnKXB9zHVlyDB26dhTMDMQR9XNaxZJGB/J51e4+is3UOIiE/IkEo\narChkSSe+v0pnPwgqjhmvH95GJv2p3JMFz4awccjScWVIRwABoZT5rZ/fHcAq2+tx3//4izLoS87\nDgvhoA8nP4hqtp38IKrrGRgJ+o1dURj0VY5BP4ZDAlb86KDGx++7vzyO7iPn4E/n1dyAVHjEeIIm\nrTJAndOQO/Vmuh3IT91qSTsDw5QJIc2+5J5Zn/nOCwCy3RaM8ifyxFNdEdDkSu67YSYqgxyivABI\nqVBW/aQI/nbxZ+HnmDJBXXtlDZ64u0UzIW45cAKtzVcYTsKyClDtVKGnaISUcl9QS9Oj8SS2fKUZ\np/tj+NbPe3DhYx6bljViJCEgHNT+WZhNCnLeK/P8TqRbpMjvOd0f07j727GqsgLlqMYOcsgpLvTt\nLgMyRQWMAT9duQAxXgDHARX+0RosvdokUYJmMO27OKTsW72qkftT6Q3SUT6JSMiX5S0oiCL6h5JY\ns3u0ZmlbWzN8DPjpH04rQgu5/UXmpLP1wDvY3tacYfOUqkvKvJZtbc1YfWs9thw4ASCVr1u7qAEr\nuw5pLKKCPk5j5iv3NzNzlzeaFMyc0etuuArVFQHE4kn4fQyXBnmNyS5HwfmSg0x+iw95D5YBVj3l\njHzr1A0M9Qpsd94zX2NGm3mMbW3NOPzuAP7Hrh7NMWMJAR8M8hpzXWWf7S0YiCY0+9m6vBk/e+O0\nMunIr33ynvkQoW1zMpIUcPFjHtNrwkqDx0uDPJ64u0UpBj7Q8QXdYz+ydC5u3vyqZltn6xz81fbf\nOvK9SwoioulVkyxMWTJvGq6YWJFqRilJ6PhZD755c70yQT/2ah+2fKWZPPZKjHy8H4mcWPpjoLtc\nBpjlqDT9kkxqk3o3LMa5D4cR8nGaFYFeL6a+S1FlhRSLJ/GT351SJhr1McNBH6bX6MvgwyE/Vmac\n64O7e/DE3S14/eSAZiUIBlQFR1c5giAimm4cqV7dbPl1L6oq/Mqx5WNlHltPgl8/ucpWHzA1I0kR\nT//bKcX1A1dPxfNvncV9N85EVYhDLC7gwsc8Fm19TXnP9TNrLTlQFCsURSEwfdzor0fkB01aZYIV\nTzmj2qQon1Qmu9amOs2EJLesUP+xdh85p4gJ3vneYmx/uU/3mLF4aqVl1HpE71yrKvx4ZOlcTK8J\n48xADFUhP0J+LuXdl3Z2T02g2WKQR5bOHc11xQVIkqR77MGRhOa4sizfTh8wNeGAD20LPm3YvsZp\ne5tihaIoBGaMVyywxjOWouqMsTVWthHFJVe9jpk0Wt7+wrHz6Ow+joFoXJmwzPYd5Y3l4OGADxPD\nAR3XimZwHHTfd+GjEdRWBcEYUBMJouvf3sW3fn5EcXaf/XcvGhZBz6gNK7mulU8fQmXAp7hnqOX2\n1RX+rPOZPCGE6pAfl2MJPPv1BfjV6hsxqTqEXQffQzRtdjs4koAgilm1ZbkcJpw6UOjJ6cfCjX0s\njpvLtWWssXo+VF5QfCzltBhjb0qSdE3GtrckSZpXsDPLg/GW05Kx8oRsxShXLxxktG/Z987omKIo\nafpfxXhBWfll9tHatKwR1SF/SryQEJTcwf4Hb0Jn93Hl6TbzZ2C09xUYNO/b//b5LLPe+26YmRUC\n1Duf7cubERckrN1zJEtkYdSXy9XPs4D9psw+70L3ufLaSs7u+VDotGBYuommkxZjrA3A3wC4AcBv\nVb+qBiBIkrQwnzMsFON10gIK+wdldcKr9HMYToo5z0HuzyVPZhqlo2rg/PP379Q0ndRrLLmtrRm1\nkSAYY5YbUKrRS7C/uvZmXSFHZ+scdHYfL3jyvVBJ/1yDtNPjWv3ueU3M4LXzGce4IsT4NwDnAXwK\nwA9V2wcBHHV2XkQhyVWvY3VgMXqd3r71Wt6brbyU/ab/zzGWVa+kzh30XRzKam9y/NyHeGzFNZhQ\nEcAQnypi3v5yHw50fEF5n6yAlAubRxKpFR8YsqT5egl2IxGJbOtklHx368HBaS4sF7mKsJ0c185q\nxWtiBq+dD2GO6aQlSdJ7AN4DcP3YnA6RC6cDohymi/LJrJqnzIEl1wBkdg5mA2Kln0N/TNtnynBg\nUw2cfzj5AZZfN0Nb67W8GVUhPz4eSeCbz745WpD863ewaVkjHtqTWl1dGuQRDvkgiRKivGB4TXoJ\ndrlDc2bSXXYd0Uu+uxn6KpTThdkgLX+2NZGAYkps5bh23Ei8Jmbw2vkQ5lgVYixljJ1gjH3EGPuY\nMTbIGPu40CdHaLHjrad+z9BIEmBAPClmtQ7RS7CbJeJznYPRgFgZ4BCNC1l9powS/OoB+65rpmPN\n7oyWJ7t7cPbyMKorAprjdR85h837e7Gzfb7i+1cTDuYUF+gl2CNBH3745aYsIcf+t88brjzcFjFk\ntiEBkLeAwUhUM5IQlM+2Yf2+VAuWobilidLOasVrYgavnQ9hjtXHiB8A+K+SJP2pkCdDmGPnaRbI\nfurv3bDY0sBiNgCpXeT1zsHsqdVum3eOY6b+fnJhcebxLnzM4/0Ph7Fo62voWDgLyxfMQG0kZHps\neZLc0d6CcDBVJPyPv0p93eXwYjTdGfjrN83MCjMCUFafhQo1ubWKMwr/iSJsfb/U2FmteM0r0Wvn\nQ5hj1UjmAk1YxcfugJj51G/U6TezhYWRjF0etM3OweipVW5jYnR8teQ4Fk9iaGR0NXHhoxHDlieP\nvtKH7cub8eram/Hn79+JV9fejH/+m2Y89mofrp9Zi3s/fxXW7Oox7XIsHwcAIiE/Gta/iEVbX1Pq\n0V3FLjwAACAASURBVBZu+Q0AoLoiAAaGKC8o8vvUSjPl3r7y6UM4ccHgGvn85eJureKMJPjhkPMJ\n1+5qxWsdi712PoQxVietQ4yxnzHG2tKhwqWMsaUFPTMiC7t9kzInGNlMN9fAEg7q1zfJT6Fm52A0\nIMbiAva/fT5rv9vamjW1VR0/69HUZN3/zGH4OYbNy5qyaqsmhgOonxRBXJDw8HPH0LD+RTz83DGI\nEvDDLzelVggVqdWd/rU34ye/O6UJc8Z48+vTnzhGuzPrHcet/lluruL0Bul8+nJRN2RirLBap/UT\nnc2SJEn3uX9K+VNOkneN6IEXbDk26El5OxbOQvvnrsSEyoBSM6Un//7xb09m1zfdOFNXHfj4imvg\n47is7sGZ1yF7F8r7jfJJRII+DCdFw5osAOm+XI0Y4gXUT67CcHy01isaT2qsq+TXyyEt9T1obarD\nA7fUK52Q+aSIBd//V837nrx3vqlgw6iGqXfDYsUZXz7OrClVOHFh1BcxXwl1oaXZXqufIsYdrnoP\ncgDWSJL0IQAwxiZCK4EnCoD+INKMJ++dj4qAtjB2KB26U08aermLtgUzEPRzgATDthiZtkSrb63H\nvZ+/Spk4q0M+pcX9SCKtSMwxkcpP4vfdOFM5T/kJP8wxZQVh1CX4P3yiEp/5zgvKIC3vO1eeLHUP\nUi7xLxw7j0uDvFLEvO/t89j/4E0aE9uKgA8Vfp9hfsMod6Puztx95BwuDfLobJ2j+A260T+rUBJ4\nmXxyO+O94Ha8X/9YYnWlleV+QY4YhcfKk3U+8nQz5PdVBlKhuzUWnCuMztHOdRqttOSC3swJ0Wgl\npfZNFAQR0XjKhT3GC4jGk5hQ4Ud/NK5I4+XrqokEs/ppZd4XvQeJzHYnRm75+a6IvDg4jvcV2ni/\nfhfJ3xFDeRFjRwDcLEnS5fTPNQB+I0nS3LxOsUCUy6RlxU6n0CEjs3Ymn6oOIRz0GZ4jJFguZJb/\n6KdMCGHtogbNZCK7XQwnRF17qcGRBEaSIjgG3Ro0vYn19b+9FR0/P5IVOv3qDVcptUlGzh56EwcA\nx2HcUme8O0qM9+t3EVfDgz8E8G+MsV8AkAB8GcD3HJ4YYYJ6QIzySU1TQyBbRlzoan6j/U+vCYOx\n0XDZpOqQsso5MxDDSFxANG6cG1KTGZYaSQhK+FHrxqGvG4oLIobjgsZyKbNFSuY1TJ5QodnW2lSH\nJfOmYVXXYU0B8+43TmP7y31Z5692AJE/LwBK2FUUpVRBdYBT5P6FXBkVcwU23h0lxvv1jzWW1IOS\nJHUBuAvABQCXACyVJOmZQp7YeCSzcHdV12Esv24GOhbOMlT75aP4soKRmu7ixyPK4Pj4imvw7Tsa\n0Nl9XFHwDcWT2HXwPcvybLWaLRz0o6pCq2wzcuGW25QY9u0yUDzKbhcyD9xSj3V7j2YVMC+6eqrh\n+ZsVWss5xYFoAqu6DlsuBneC3nkMjiQ0ZQOFdFG3+x30msN7vhT6b5DQYrnhtyRJ/y5J0r9IkvTP\nkiT9eyFParyiJ6des7sHX73hKrzzvcV48t75qEwX28p/7IWu5uc4ZLUW2bSsERMqA8rTvI9jeGhP\nxoC/qwftn7sSrU11yr6sPn1mDmqCIBpODvJTrlkdVqWfy7pHE8MBbG9rVrYZCUBmTanCn79/J/Y/\neBOmTAhpzj9X3dRYtRbJPM6k6hAG+WRGLVlhJktZAPTE3S2mD1fq99hxdSmFCY4cNcYWSzmtUqOU\nclrqsA4A0/yQUbIXsJY7cnR+FlrFm8nA3788jM0vpQQJVp3CM69zW1szdh88rQmTyvsCUq1IJlWH\ndJ3fdx88jbYFn0ZNOJCVn1LfN3UjTPUxHlk6Fwu3/EZXqGGWc4ylZfmFbvEhn78sre8+cs64dYuL\nORajz8ko9yhjJ/9TSgIHLwpkShBLN8zySsvxWTDmY4y9xRj7/9I/X8UYO5j2MvwZYyyY3h5K/9yX\n/v2Vqn08nN7eyxhbVOhzHisynzpP98cMwwxmT+2FrOZXt4r/zHdewKKtr+HCx7wm9GEUQuy7OIR1\ne4/igVvqcz59yk/Uapso9apt0dVTNa+XV22ypP3SII8tv+7FI0vn4p3vLcYP/roRtZEgthw4gdW7\n3sJwUsy6R+r7Fgn6s56Wty1vxrSJlUpDyIf2HE3ZN+W47vcvD2Pl04cwNGLcIDNfMr87nd3Hsfb2\nBrQ21RmuGt3MsehGBXb1YDghmn4H7eR/itUE0wnkqDF2FHzSArAGgNoCaiOAf5IkaRaAywC+lt7+\nNQCXJUmqB/BP6deBMfafACwHMAfAHQD+N2OsLNbdmX+UskO5XphhrJK9meEYvdBa5uSjF0LceFcj\nHn2lTwmxmTkkqAfgSoPrrJ9cpdkmD/4cl5pwHlk6Fz/8cjP4pIgHd/fg2784inMfjli+T5mODk/c\n3YLdb5zGZ/9+nzIhTJkQQjhkft2bljWCYykhyFO/P4VtqhCkm2EjvQFdfkDIzNep75dbOP0+2sn/\nkMCB0KOgekzG2DQAf4WU0rCDMcYA3IpUY0kAeBpAJ4DHAHwp/W8A+AWAf0m//ksAdkuSxAM4xRjr\nA3AdgNcLee5jQeYfZfeRc+AYdJVzQ2k/wEK2TzDrTqxXcKqu5aoK+fHYimtQXRHAuQ+HwTHgn77S\njI7bZmMkYX6O6gFYzwBXzk1dP7NWt6i2IuBDJOTDih8dVH6/eVkTNu77PznvU2Z/r0o/hyifxP3P\njIYK5QnhkaVzNfupCPiweX8vOlvnKKHTzft78cMvNwMAtr/ch/92S73S4iOa0cMrH4wG9FlTqjCS\nEJSC6kIUIQPO23nYKZCmliGEHoX+5LcC+DZSnY4BoBbAh5IkJdM/nwVwRfrfVwA4AwCSJCUZYx+l\nX38FgD+o9ql+T0mj90d54WMeYNC0ogDcdUMwir9bcZE3KmpefWs9vnbjTAyNJMAYsHaPultws9KR\nWA/1ACx792V2G44EjV0qUqukkPL7oZFUU8gXjp1Hx8JZiptHZuNH3bzM8mbURIK6E8KM2nCq4EP1\n+cmhU5nrZ9ai7+IQAGD1rfUYyOgfZiXvY4VcA7qZq4cbOP0+2nHdKLQDCFGaFEyIwRj7LwDulCTp\nvzHGbgawFsBXAbyeDgGCMTYdwAuSJM1ljB0HsEiSpLPp3/0ZqRXVP6Tf82x6+5Pp9+zNON4qAKsA\nYMaMGS3vvfdeQa7LTewmmt1I9podE8xYCJIpHDBKqO9ob9EIGlqb6tBx22zMqA0r5yxJqeuQVx8B\njuGrTx0yfY+d6zRz87DSVv6xFddoGkvK23e2z9dYX+ndy03LGrF5fy8ufMzjibtbNCs2eT9G7h52\n8IJIYSzEByRwGFe4WlzshM8DaGWM3QmgAsAEpFZen2SM+dOrrWkAzqVffxbAdABnGWN+AJ8AMKDa\nLqN+j4IkSTsA7ABS6sGCXJHL2PV6M2p3bwez1RQAy+EYo/CU2guwtakuS9H3+IprwAti1upjZ3sL\nVqYLey8N8oiE/KlCXQfXKd+nIT6pNJ3MvNaqkN/wGqorArqrvcxcStbnxwvgOGDLV5oV9aBRfs5O\nryqjayx2Dyg3vo9eOAZRWhRMiCFJ0sOSJE2TJOlKpIQUL0uS9H8DeAXAX6dfdg+AX6b/3Z3+Genf\nvyylloHdAJan1YVXAZgF4I1CnfdYM9aqI7Pktp16E6OEuroXl17B7uVYIqt78ZpdPRAlYEd7i6tt\nLXIl8o2uoe/iEDa/lMpV9W5YjB3tLYbno/n8KvwIB0c/S7P9A8CUCSFAguMapLH67pRCrRQxfhgL\n9WAm65ASZfQhlbN6Mr39SQC16e0dAP4WACRJOg7g5wD+HcA+AA9IkuQ9zasH0RtszNRbej2RasIp\nU9zMActsgpO360mvjZwrqir8iNgYgK0MpJnX2tpUhwMdXwCQCm9W+DhsW96cJXPf//Z5vHDsPDq7\nj2MgGleMd+2id49kVWVrUx3WLmooeAFwvtgtBiaIQkPFxR7DrRi+mRJwIJawlAtx6iAvb4cErOzS\n5oxeXXuzxiMQGM0XgVkLAVnN51gx4j387gBmTqpW1H8nLw3ihlmTcnoFmn1O6t+NJASIIhAOjQpE\ntr/chwMdX9C/Dx4zWSUzWGIMcc/lvdQo1UnLzeS62WBT6ec0QohwwAefL3vRne+AlboeXiu9Xt6M\nuCBh7Z4jGsVebVUQw3FRtyllPudlNoFeP7MWP/jrRsTiqeaSf/loGKIEXDGx0oIrfcZ1tTWjNhIC\nYM25BLAueikmVjoNEIRLeMMRg7DOSDLVUPHZry9QXBicOgAY5XMqAxwGYqMmrqu6DmMgltAN9+Rb\n3MlxDJFQqvC3d8NidLbOwT/+6k/Ye/gMHltxDXo3LMbj6SLehvX7sLLLWujJ6nmpVzzhkP57rphY\nic7u4/jWz3sgAfj2L46qwmC8YdhxdUZebvWunlRDzHgSNZEgOlvn4M65Uw2dS0rFZLVUzpMYP9Ck\n5RFEUUKUT+Lh546hYX3KlmfdHZ/NMmm1itlgY9Uax40Bq8LvQyTkx4ofHcRfbf8tLg3ySvfk4biA\nbzxzGFsOnLBl02PlvKxaZJ3uj+H1k/345s31Waa/q3f1ZF2rPIk9+/UF2P/gTYoh8JQJIUTjKf9C\n+fOTbZX0JlSvmqw6cUQhiLGEgtIeQf30DqTk2Wv3HMGWLzc5cgAwKszM1Z7eyj7sDFhm0mxRkhyt\n5KycV6a0X7bIeiij6Pl7v0o5jBn69alsm/TCtxvvagQAPLhwdtbnt27vUXS2zsGlQT7rM3QqWbeS\n88ynW7UdRxSCKAY0aXkEo/DVlE9UaFwYrGI0KNqxxnGrFsio1sapTY+V87JikcWxtAMJYGgfFeMF\npaBYr8ZNtneaUauviqyfXGU40dutQbKS88wnL2rHEYUgigWFBz2CkWN4qmDV2VOt3IhQLnSVvfWy\nwz3N4Jh+vVAha4HyCZHlOi+9EGKmRVaFf/T4j73ap29+q/oLMcqlzagNK12m1aQm4KRrLhVGrufR\neGZTTGfO6GRQS5QC9NjkEWTHcHX4KnPQNMJMep4z3MMLEEQRX3vqkCt2QHZCU4V0dbASQsw8/nBc\nwJYvN2HyhAqcGYihOj2xydcVjSfRu2Ex+i6O9q669soanLgwhM7u49i2fNQod9Qz0b2J3nhS8aM/\nGkdtJJjXxFPqBrVk+TQ+IMm7RxBFCYMjCVyOJTC9JowzAzFMDAdQXREw/cMzCwfFEoIiDW9tqsMD\nt6QaOcbiSWUwdbMOp9B+eHYHJUEQLUn7c+3fKJf1/FtnsWTeNE2TS9nRvRCDpplXYte/vYv7bpwJ\nAI4/Ty/4GTqllM+dUKA6rVLDyZOi4aSTzt3M/rsXcefcqVkegE5McnNRyEJUJ+bCha55e2zFNfju\nL4+j+0jKCtPt+qXM70Oln8sqDFdPnldMrAADy+u6S3W1QkXQZUHRDXMJmzgxBzUMB4V8Sp5M7QEI\nODfJlTEa2AqZE7EiEsjn9WaYGevKExaQLdzIB7PQ7o72FoSDfsUjsfvIObx+cgA72ltQXRHIK+Ra\nqga1lI8bP5AQo8Qxqlk63R8DxwHb2+aZtl+3K4Yw86JTm+XKrL61HlEXzFbtDkr5DmLqeiW967r2\nyhoMpRtTGgk38sFIUDGcFBEJ+dGw/kUs2vqaMmnKDvvA+Gz9TkXQ4weatEqc1KTTnGXKuvXAO6gI\n+FK5rbj+oGtkkmsWSjJTp4WDPmy8a1SB17FwFto/dyX6h+KQJOCDQR6DI/ruG7mwMyiJooShEeNr\nzkXmxPyT353KMtbd3tYMH4Pi9vHI0rka4Ua+mE26NEBn49VibcJ9KKdVBsTiSXwUS2DKJyoQ4wV8\nNBzH3sNncd+NM1EV8rua3zHzoovFBfz4tyex6OqpqJ9cheF4Eh8OJ7IUkTWRIMLBwok8hvgkfvzb\nk1gyb5omj7etrRmfioQc5Qk7Fs7CV2+4SiOyAFCwQl+zHE044CPRgQ6lmo8jFEiIMV4QBDHVoXe3\nqrHi8lRbd1kt59YftJ3BtOe7t+ua1GZ2ALaK1WuQJ9Y7505VFJN9F4dQPzkCn4X4nVsmsfk8LDh1\n2C8VSv38iYJAk9Z4YSyVU3YGUyA/ZaK8r8oAh1hcsCwlz7wfrU116LhtNmbUhh29H3B2P91wyS/1\ngV3vGgBjJ/xSuz7CVcjlfbwwlsopOzkwIwFDjLeeV/rxb0/i/csjiiv9yqcP4YMoj5iJuEOd31jS\nXIdv39GAh587ZrmJoVv5ETdc8ktZUGEk2hlJOnftIAiatMqAsU7MGw2mgiCmnMEDPpy4MITfnbiE\nbW3ZAgZL7gxpwceiq6cqcn15gFuzqwcXB3nDSUg9sW5YMhcP7TmKSdUh/Gr1jXj26wsQ5ZMYSRoI\nOPgkwIDKgA9P3mtNnGJ4DWUmmLDSLVqNkWhHFFHy8nS794JwD5q0yoB8VwZu/AGKooT+WBz3PzPa\nmmNO3Sdx+N1U/dDo4J9bCAGMrlKM5PrTa8KmT+nyxBoO+VJdi29vQGf3cTSsfxEPP3csJcNXXWfW\nqqDrEKK8AEl+DYPte1NOijazUgf595nfIbMawlKezHPdC6Kw0KRVBtiVratx6w8wlhCwJqMx4rq9\nRzFzUjUiDkJc8ipFdl9XI2+XkZ/S9SaVWFzAgwtnZ63WVu/q0Ux0xma0gqV7ozdoZ34uO9pbUBMJ\nIJYQSm6AMyt1MPoOmZlAl/Jkno8pMZE/NGl5ECcrH6f5D7f+AI2eqlNehw46L6dXKfvfPo+tGTVS\nm5Y14tFX+pTXyqa1epNKOOAzbBuiDkcZnX8k5Nfcm10H30u5qqs+G7OJX3ba7x+KpxtE7ivJJ3PT\nujGD75Bc3J41OQV9jh+yvAC5bxSX0vFpGSeMtfGn2R/gUNpk1oo8OxpPpmq10nViG/f14tIgjyif\ndKRglFcp9904ExV+Dk/cnTKiPffhMCoCHC4N8vBzTPHf2/xSr65VE8cxpdDYzKrKyOFcvaJrbarD\nknnTsKrrsOazqQz4TC2j3LSUKhZmDvBG36GKgA8Vfp+hpVQp2kUBpe+GX+rQSstjjHXowUgsYLRy\nySQ1yfKj6r6uQ5AAfPe//kc8tuIaRILOZdry6tHv41AV8mM4IeCKiZUIB/3Y2Z56Su9snaP47wH6\nocJwMHduSS//tK2tGfvfPq+8Ru3hqP5sjBp4hoM+JbczZUII+x+8CX/+/p3Y/+BNmDIhVFJP5mb5\nOTPBSakrIPUop1xlKUJ1Wh7DrcJWy8czaLuhbrdhtiIwqkV6ZOlcfKoqZKuI2G5dktGxO1vnoLP7\nuO1i3Fyu6r0bFqNhffZnY1RE/cjSuYiE/IgEfRiIxV1xBik0ZvfJbt+2YoX8xqK+rRxq6DwIFReX\nIsVosaD+AzxxYbTBIZB7wjSaZHs3LAZLdwnWO47egNgf5bF6V49q4Gs2VRvmO+HavTdRPolVXYez\nPpsn752PKC9ozmNr2pHk7OVh1FYFdd/n1BmkUOTr4OGFQdxrEyhhCyouLkWKEXqQQzixuIDO7uPZ\n7TZMhBRGoaEzAzHN+3KpFGNxAasz1Ierd/WYHjtTnWcUKsyFmfBFHd6KBP26n02FPy0saJ+P3g2L\n8fiKFvzsjdP47N/vw8PPHUMk5DeUfnuJfELTXgkDkrKv/PHOYx4BoLAt6HNhpUW9/nuaNSukTcsa\nUR3ya96XS4xgmBcKmQtC5MFyiE+is/u47eS4nSfznJ8NA84MxPDwc8c013m6P1YSiftyUMWVwzUQ\n5tBKy4MU66nVSb1X6j0hRRixs30+aiJBVFcENO/LNZiY1fQU0nrJ7pO53mcjihJi8SQgATNqw+hs\nnYPWpjrlPVsPvJPVPsaLiftSc/DQWyEbXgMvkINFmeCdxzzCEzjpXMtxTMnNGOVocsmE/Rzw+N0t\nqAqlOvLuf/s8lrZMw0fDcUsScacrVDeaRQ6OJDDIJzVCi413NQIAuo+cw4WPeURC/qKsnu3gZKVd\nLMw6O2dfQzMEUcQ3nn2T8lxlAAkxxginiWqvJLjzxSwMByBLhLFteTNCfg5//8tUjq1QCkoj4cuO\n9hZLrvJDfBIfDPKakKC8Dz0Vo9cple9brhY56mvgGPC1p8ZW3EQ4goQYXsGpVVI5eZyZhR5TITqt\nCGPN7h58PJJURBWFClPp1mctb8ZPfnfK0j0PB32YXqPvuDFrSlXJuT3IDh5y0bBXLafMVsiZIdyK\nAOW5ygmatMYAp4qmclNCGeXqjAaguk9WFjwHpOcPuPuN09hy4ISlex6LCzgzEDPMBZVaQW2pPCjZ\nyb+VWq6OMIcmrTHAad7EjXzLWCefnRzTeFBJjok3nUbWHvJj+8t9mt+b3fNwwIeJ4QA2LWvMbsHi\nwVxQLkrlQcmO8IYcLMoLCuiOAU69yvLxOCtGkaXTYxoJACLB0VXZWGH3nnMcQ3VFAAE/h53t8xEO\n+RDjBSVMVWqUimTcjvCmmGUkhPvQSmsMcPqkl88TYjGemJ0e02lrFSurOrsrPyf3nOMYwkE/qirS\nk2xFaYUE1RQrlFbozgZeKX4m8ofUg2PEWKsHx9rDMNcxlcS+S0+5VlZ1Tld+TnwK3X5y1/NBHP7/\n2zv3KKmu68x/u6of9APZBoECFjJCrSErkFbLECsaRY6kSEb2rGlrBWssxnoQK3rYcsBLkYOd0ZpF\n/EiC0SKChLEFYwUjPKCl4FGYhAhLg15mFCIgLRBRkNrCAgLhKRt1V3d1V9WZP+reoh73VffWfdb3\nW4tF9+37OPd09dnn7P2dvXMF31cKcVqhk8RB9WCUcDvTc10nK4QZs9kzh0ZzFYH9M8NZ5AsFT3E2\nJ6s6Lys/qz73W6xgdv8nX33Xd3GEl4KibolLHI1EAxqthBJG8NmsvMeGXYcr5eybBzB4atjT4Osk\n9uJXfMbvQdbo/ku3DGDB3GmBDOpBu9LiEkcj0YBCjITiR/DZziVm9MyO1pShGq9narenYohOBBON\nKNZn9M5+D7JWVaD9eF7YsKgiqQeutBJMI2fMTl1i1c8cGS8Yugz1isBuB18nK0mvq02zdx4d99f1\nauZmHRnLY8dXP4n+q6Ynap8RJemkHijEaDLcCgic1PkyujcA32pe+S2YMH3nu+djZDzvm3DASJiw\n8vZePLbjEE6ez5ay6FcnJY4zcUkfRXyFRSBJJZ6K/NmoEY3uvXpRsRDiyFgBqRQwoTWNodEcNuw6\njDU7ByOvErN6ZygEph48cjaDVc+/XUppFcUCkoQ0AKoH406jM1p4ERDYqRENxQO64GLjHgxn84Aq\nZo7/4vWzKpRpACJVNkLvd9NyKWN5165Xp7/T8mz7N696uaIwZxQLSDY7YWSfaVZotCKKH7JqLwIC\nu7iDlXig3DhWD/YAIpXrrrzfH332gEF6pspYSz2DlZvfaVLz5iVpkI9LvsakQKMVUfyQVXsZAO32\n75jd205wEbU9OuXteXbgOL773CH82e/+uuE71ztYWb2r2SCeRJFC0gb5qH2Gkw6NVkTxQ1btdQC0\ncokZ3XvFwl6sfbEodzczjmHt0TE1ElXt2fbGcdy86mUAqKhUPJTNAQIMZ3OYMrHd0WBl9q4drSnT\nQTyMzb5+k7RBnvvMgoWR3Ijix94VPxOHVt9bF1xsP3DC0jiGsUfHSpCSGbduj9G15VWKrQYrq3fV\nB3EANfvX3FSTDhM7JWDSBnnuMwsWrrQiil9uIT+zHVTfu1pwYfSsMNxfVjN9u/YYXbts6348dGMP\nAGt3q9m9u9pbEjOIO3H9JS1Ol0QXbpSh5D3CNMvelaDf04l836w9Ztce+vancef/3I01i67GpM5W\n0+S2RvfOjOdt98DFBaf7+ZKWILdZ/lZ9xlGHxesvosmIm1vILUG/p507x6o9ZteOjOWx/p756GhJ\n4Vxm3HRANrq3WT2xOM7UjVx/l1zUDqiiwdcH9KTVt2qWv9UowJUWaTo8bbK2udbJSsPsvkmYqVe/\nf/9V0/FHt87G157Zn5hVFfENZsQgxAwvRsKN+9DPOmZRotqov/Dwb+MbPz6QCNcn8R26B0lzY2Vc\nrNw5lkbJ5mfDY7mmVpJVq0gBJEZkQqIB1YOkYUQpy4HbDaz5fAFnhrOG11ndU//ZX//0MFYstM6i\nkXTKVaRJUwqS8KF7MCSiGsMwa5dde+uNE7l5/3qucRNb0o3uA0/tNbwOgGnWdwWFzrYWDJ4awms/\nO4Nrr7gYPVO7kRnLoautxdFKLQgCV2omUClIfIPuwagS1T9ks3ZN6mw1UMT1oau9BRNai4MfFCw3\nyDp5jtX713uNmw2smfG87Z4pw5+1p/GF9btrSq9sP3CiIpZlmQl/vNCwuJrVNUF/7vzc0E6aE7oH\nQ6ARaWzcuuKsrrNqV+3xAZw6ny25yTrbnRsJN+9f7zVu3FKdbWkMnhoyvc7snkfOZgw3G1c/zzIT\nfh3599y6PsNKn+TnhnbSfNBohYDXNDZuBy2768zaZbb6mDGpszT4HTmbcWwk3Lx/PdcUCgopAdYs\n6qsrtpQZy2PHmydqYlKrF/WhszVtkvmgD4+/8HZNu3qmdtdWUnaYCd8Ot8YnaemTSHNCoxUCXoPT\nbgctu+vM2jWczVlmcAeAx19427GRcPP+Tq/RDfO9G/bgO3//1oUM7XfbJ5rtbE1j0TUfw7P/fAzL\n++fg0Lc/jSfumofJnRc2Blcnr+1qb8HJ81mDduVqnuc2E35NO10aH4oiSBKgECMEvMYW3O4FclN9\n2CymtfL2Xnz3uUMV1XR/sHg+Cgq2sQs/Y1puN/eWP6eeWFF1u5bc1IPF112O7gkthpJ4o2S7O//1\npKlwwwgvG5jPDo9h8+73sGDuNPRM7cZwNoeutjTSac5fSehwc3GU8aLicjtoOc0LZ6sezOaRLxTw\n4KZ9rgP6fqkHrQxzZswf1ZzeLr3EyNLNA6b9Uv4OQ6M57Bo8jTnTP4xlW51njPAy6cnnCzibW85o\nRgAAHBlJREFUsW5jnAlbnUk8QaOVVNwOWo1Uj0V1cDAzzE/cNQ8PPLXXs2rPzbPNJhP6ZuT7NxpL\n7P1I++R1JRploqrKJY6h0UoybgetqBqbRmEmK9+y+whWvfBO6bxrZ03G8v45WL7tYMMGNjdu26BX\nhklIM2X2GU6yQW4SHH0A6ciOKW5lxEmXH5tV+l2zc7DiPDeqPTsy2cYJTIZGc47UofVufYi7GMNK\nAUt1ZHNAo0UaQpRSOFUb5pHxgiPVnpe2FwoK+UIBK2+vTuHUZymzN5LRr17Uhw27DtuqQ+vd+lAo\nKEABP7rvGrz0yA24rW967NJMWSlg426QiTO4ZiaeiXoswahelZ61AriwQfjmVS+7bntmPI8HN+3D\nlIntWN4/Bz1Tu3H0XAZdNqvZVEowqbMV6+6eh672Fgxnc+hoTRuuDKtXDOUDOOAmC4mW1aQlPi5i\ny9WUQmLqkhFzaLSIY8xiCfUMnmFQnUpoaDSHDbsOY/uBE7h21uSSfL985m6Xo7C6H/TBNFdQpW0A\neqxoKJuzlP9XbydYvagPS27qqYjBGWWKr8cdZvw7GsD6e+ZbqhSjFv+0K+DJlFHJh+5B4oi4xxKq\nXYZfvH5WadPxYzsu7DcDrNtu1g9m8ax3Tg5Zuu3MUjstvu5y243a9bjD6v0duc264gUnLmbjrCQX\n+ibpMVtCo0UckqRYQvnABoFJRguTnIYm/ZBKoWYwXbGwF2tfHLQUe5gZk+4JLTVikuoB2G4Ar2h3\nnSKRoPMUOjWSZkIbGqfmgUaLOMJqpm4mJuhoTYUiyqhHFFLPwA+Y98OE1nTFYLq8fw4e+8mFFZzZ\nqsYsRdZwNme7YnA6gLsRiQS9eq7HSHI11dz4FnAQkRkANgL4FQAFAOuUUqtFZBKApwHMBPBzAP9F\nKfW+iAiA1QA+AyADYLFSap92r3sAPKrd+ttKqR/61W5iTD2xBD1mtGbnYOCijHpFIValM4xiOplx\n637obm/BUDaH5dsOOqpenBbBytt78bVnLmTEWHl7L9IO90ylUlJsl8WeLjciEbvfd6OJg4uZRAPf\nNheLyDQA05RS+0RkIoC9AG4DsBjAOaXUn4vI1wF8RCm1TEQ+A+APUDRa1wBYrZS6RjNyewDMB6C0\n+8xTSr1v9uxm2FzsBi+B9aBy/3mlUc+vr7ZYbaomp4azoBQefnoAX7qhBz1TuzF4agjfe2kQqz7f\n52izr5Nnudr0HLAiNOzPDYkE0cqIISJ/C+CvtH83KKVOaIbtJaXUbBF5Qvt6s3b+IQA36P+UUg9o\nxyvOM4JGq5ZGDEJO8hICCDXjQj0DtJURtxpE9RWXVRXn0VwehQLQ2V7M1djZZjxBGBrN4b6NxtWQ\nuyfYD9ZOBnsvCXaDUg9GfdsECYToZMQQkZkArgawG8AlSqkTAKD9P1U77aMAjpZddkw7Znac1EEj\nAutGsYTqAHo9dbX8wCrDRHlsyzjwn0VmLGeriLSKqZSXRun75k/whfW7MWLRx51taYOSLn2O3WJO\n3Gr1xu103MaO3Gw0p8CCOMV3oyUi3QC2AviqUuq81akGx5TF8ern3C8ie0Rkz+nTp901NqH4KUuv\nNoarnn/bIOAf3AbPztY0VlcZgRULe7Fh12FkxvOlATUzZl6N2UrCbmd8650cFAfr9qrBut3xYO1E\nuRmkQfAilY+jwCJKmWCaBV+Nloi0omiwfqSU+rF2+KTmFtTjXqe048cAzCi7/FIAxy2OV6CUWqeU\nmq+Umj9lypTGvkiM0QcRv1ZA1cZw2xvH8diOQ1h/dzgzZn2A1os46iq+NTsH0dmWLg2oHSZGfMak\nTlMJ+5pFV6OjJWU5SLmZHHgZrJ2uooIyCEFL5cMkjL1sxF/1oAD4AYC3lFKryn60DcA9AP5c+/9v\ny45/RUS2oCjE+KUW99oB4E9F5CPaeZ8C8A2/2p009EFkysR2rFjYW1O3yesKyEhldvJ8FhCUBsig\nGRkv1Kj3rp01GcPZXGlAHTw1ZKiOGzw1VJKwT2hJV6gKO1pStiIMO9Vdo+NEVurHMHBitKOYacMN\nUc8Ek1T8XGldB+AuADeJyID27zMoGqtbROQdALdo3wPAdgDvAhgEsB7AlwFAKXUOwLcAvK79+6Z2\njDhAH0S2vXEcj/3kUGkF4qT8vKP7u4yX+IlRm75/58chADb9/jXY8dVP4rWfncGKhb01bsS1Lw6W\njEz56kQXX9itIqz6w6+ZeZTcanbuyiStTijTDwfW00o4QUiJq2fOHS0pjOQKgc2kjWbuAErHRsfz\n2irrQrVevcz9gjm/gks+NAFHzmbw+Atv4+T5rKmEfVJXG2Y/aqxMhIJhdeKo1Xvye5VjpwKMQh80\niiS9S0SIjnqQhEcQKyF9pg8FQAGSEpz5IIuHnx7wfSZtNnMHUFp9FBSwZPNAxQpp2db9uGH2VLSk\nU1AFhYsntmPV5/sMY3D6Ckt3KZajZ4gvf0ezlY/VzDyIYH4Qqxw70YdVHwQhamjkM6LoZWgGaLQS\nTlDKsdKAuLE4IH7jxwfw8C2zMWViu6+BeEcuO5OB8rLJnZjc1YZ0OmXpXtOvX/vioKFLcdXzbzt6\nR68FH70SlEjCyl1p1gej43nfDWqjjTZl+uFAo9UEOIl5eJ2BGg2Iy7bux0M39vjq53cSV7CKszgZ\nYPTrq+OC37vz46X8gk7e0UvBx0YQhRiM2eqkUIDvBtWt0bb624hSPLFZoOM1AKKulmpENgKzAbFn\narevOeuc5MgzKgJZjxun/PrtB07g9AfZUg0uPSGuk3c0Uvp1tKYcFXxsBEHnEzTCTO0Ige8G1Y3R\nZqaO6MGVls/EQS3ViBmoWbbyo+cyvvr5jWfufUgJSjNjAJ7cOPpA+4PF8zHw3z+FH913DS6a0Iqe\nKV24rW86XnrkBvzovmsABdvfa/XMfGS8EFgGkajEYIxWJ0GUt3HzjGbadxYXqB70mTgojBqRUHXJ\nTT244xOXYemWgbIZaTDl3CtWstk88oUCHty0r6EzY/19N+9+DwvmTkPP1G4MZ3NICXDfxr2e8jkG\nOZOP6qo/iH5w8ww3fxvENY46NBqjZoKJQhzBDjduo+qNlXpp+HV3z0NXe0ugA2JJvQgAAjy4aZ+n\nDZ9mJUk2734Pt119acUG7dV39GHKxPaKWXg9zwp6c3B5X0Vl0gQE0w9unhEFl2pUiMqEh+5Bn4lD\nVV83biMjY7xm52CxRlNVUDrI/GxeJwlm7tzOtjQWzJ2GZVv3V7iKlm4ZwEM39rh6lg6D+UWC6Id6\nnxEVl2rYRCnMQaPlM2F96OsxFHbSXaN7OTXGQX/YTduVzTsymGYxjOFsDj1Tu03FJhXPatCEhMlY\nw4ey9iJRiu3RaPlMGB96N4bCbAZqdq+OlpQjY+zmw+5lsC5OEiqzvK+8vRePPnvAUT9YrdSsxCaN\nnpBEaWbb7HAlHK0wB4UYCaSR4g8vxRCB+gPZjirx2vjWM2M5nDqfxWWTO3HkbAarnn+7JE236wer\n9+1oSeFsZgxLN1eJTdpaMKHBfn43v8OoxBy8kpT3SBIBCcqYxqlZaeSsyG0xRJ16Y3pmK7PRXNG9\nly8UcGY4a7kCmdCaxs2rXoZSwM2rXi4ZLCf9YOXOTadTuLirvVR25c9+99fxnb9/C/f+cA/ODo01\ndHC1TflUteJKysrM7D3y+UKortJmd9VGKbZHo5VAGin+8Hqvej/sRoP1rXMvQS6v0NGaxgejOWzZ\nfcTS3ai3+fgvRupuu507N5USQIAvrN+NGx57Cc8OHPcne4NJv79zcsjQIEUp5uAFo/fYvPs9nM2E\nZ5CTMiHwQpRiezRaCaSRsyKv96r3w149WPdfNR2fnjsNDzy1F7Mf/Qd8adM+3Hb1pei/anrpHKPy\n8t+/8+PoaEsZVFHuq2l79SwagOUKstqw9l81Hcv755iugtxg1O966ZR68itGaWuFEdV939GaqnmP\nBXOnYWlVwuMgDXJSJgReiUpsr7k2GjQJjdzz0oh71bM3qDrl0sO3/Acs3TJQse9q2db9WN4/xzSF\nUiolSKdSeHDTPkyZ2I7l/XPQM7UbR89lMLG9paaMil1hx2rK9+70XzUdj3xqdk1xTa+z0Op+f+fk\nUCnPIWCeX9FqP1HUYkVG8cvVi/qw5Kae0r4/AKaqzaAMclwnBEmFK62E0shZkdG9/PDx64Pq5O42\nrLt7Hg59+1ZcNrnTVGZutfLrbL9Q/HLB46/gij/ejsdfeBsfZKsyqmeKWS7qmUWXr4IeurGnZu9W\no2bher9nxvJYvu1gRWyu2s1ptyK2c3GFEbMxWsEs3TyAxdddXvEeZqrNoPY6xmGvZTNB9SCpGz9S\n7pjds6M1jfs21qqW7DJvGKmdXnrkBnzjxwdq7rW8fw4WPP5K6ZiTND3lqxa/0/w47W+rlZSdCjSM\npLBWytLMmLfVcEPbyaS5QUH1YJSJsxrJDx+/2T1TKRiW8+hsTVuuIo1WHlartnKczKLLV0F+z8Kd\nxgWtVtdWLq6wYjZWfVf+Hul0KlQRQJRECIQxrVCI+8ytozVVihMNnhrC2hcHsf3ACU8+frNBdUJr\nGhNa0nXH1IxicZmscdxnOJvDtbMmey5bUu/19cSYvOYMtIp5hRWzqafvws6ZGPbzyQXoHgyBOGR+\nN6NQUDgznK3YYLtiYS+e/edj+OL1s1y3P4g+MZssTOpsxUiuULdAQTc6Ha0pZMbypu5KI+MEIPDs\n7mbPy4znQ/s8Rk0cQkLF0S+eRisE4lzuwMy4PHHXPE+Cj6BWn40aJPP5AoY1QzV4agg73jyBRdd8\nzDDOZPReXe1p3LshWENh9u5xX/mTxMDSJFElruUOCgVl6krqntDiyeAGVaKjEW6eQkHVpHNasbAX\nm3e/V7ParC7hUipfcvf8wF1yZu8edHkUQrxAIUYIRCklilP02fiRs5mml/9mxvM1m12Xbd2PBXOn\n1Rgd03hRezpS/RiVjaOE2BHdaX2CiePMVl8xTJnYjhULe2s203o1uH7J6P2Il5gZop6p3TWrZdNV\ndTbvWsBBSDNDoxUScVMj6QO1HofT1YMjmvrMqzEwdaO5jPH4GacxM0TD2VxNW00Vcm1pdLbVr4ok\npNmJ/mhJIoE+UE+Z2I6HbuwppUWaelG7r6sXtzGezHgem3e/VyHNN4o5uWqrgSFavagPXQbG225V\nHbWJC9V8JOpE4y+FRB49Ce0H2Ry+9ky5a7APE1oasNJqsDilozWF266+tMKNuWJhLzpavYdx63Xv\nxmVVTRUhiQMUYhBH6Elov/ZMdZ69AceZE6yygDRanJIZy9fkBFy2dX/DhA5JFC5UZ8aYMrEdw9kc\nIIhF1pY4Z5khzonutI8YEqb7Rk9CW45TF57dLL7R4pSu9hbDtnbVudJpJndZuYvWr+z1fsFVYvPA\nlVaMCLsYnZc8e07y2zVy9dKInIBh93fQlPeZn9nr/YA1r5oHGq0YEfYfphcXXtD57Rrhbgy7v4Om\nvM+CqGHVSHcea141D3QPxoiw/zC9uPDqEVqY5eqrx01X3dbhbK74/1jx/5Hxgu09wu7voCnvsxGf\ns7Y02p0X1ywzpH640ooRUShG59aF53TlUxzMshUuuQ9Gx2uOnRnOIl8oWM7QUykp1ooaGsP9G/di\n9qPP4f6Ne/Fv74/iyVfftXX1+dnfURUN6L/fzjZ/s7Y0ehUbxywzxB1MmBsj4h5sdiJqGBrN1RR9\ntCreuHzbQcs+MEvwq19rtXnZr/52e9+gRSF+Ps+PpNHNJJpJKEyYmzTK3Td25TCiiJP9SkYKxRmT\nzIs32mXOsEq5ZOfq8yvdlpvsH2FMWPzcX+aHOy8u++GIN+gejBm6y+vc8Dju37g3cao2vVBjOUfP\nGSfpHTw1BMA6zmTm4hs8NVRXheJG7sdyEytLmiiE7jziFhqtGJK0AaycVApYeXtvxWDWPSGN1Yv6\nKo6tWNiLtS8OArCOMxkNjisW9mLHmydCGyTdxMqSJgphCXviFsa0Ykici0jaUSgofDA6jvcz45gx\nqRNHz2Xwkc5WdLe3lKoLD43msGHXYazZOejITVYe69BVhE7Ug37hxtUX52rXhDiElYuTStIHMLuA\nehIC7vW+Q9xFOF5Jwu+c2EKjlVSafQBLCm4MV9wHbjfvwM9700CjlWSSMIA1M804ELt956R7FkgJ\nRx98CjFiSpKyjEd1o62fJFlMY4bbd06aCIV4g0aLhEqzJaXVacaB2O07RyETDIkONFokVJpxxQG4\nG4jjviJ1a3y4p4uUw5gWCZSaWFxbOrHyfSvqje8kIQbm5R0Yw20KKMQg0cJo0Hrirnl44Km9TRlk\nr2cgTooYgcaHWEAhBokWRq7ADbsO12S7aBbXjxMxje4STEoMzOqd4+7+JMFAo0UCw2jgXbNzkOl8\nTCgXqbxzcihRYoRqA5XPF5pSkEPqh0aLBIZZIH5kvJAY+X4jKV+Zrn1xECsW9iZiRWqkGB0ea05B\nDqmf+DjDSezRVWDVgfg4DrxBUL4y3fbGcQDA8v45uPKS7ljHg4xKs3S1tyTC/Un8h0aLBIZf9amS\nSnXNqW1vHMfpD7KxE19UY+Qm1kvFNLK+FkkmdA+SQElSJg+/8Wt/UtiCByM38Y43TzStIIfUByXv\nhESYRkvEo7Dfy6wNkzpbS+VnuApvSrhPixBSidf9Xo0yotyvRQxw9AGgs5gYwkElmXjZ79XIVZru\nJgbAmBWpC8a0SA3NmsS2GfCSfLZZ80SSaEGjRWrg4JRcvIg7kpKVg8QbrstJDRyckouXbQfVEnyA\nsnQSPFxpkRpYvyjZuN12wBIhJApQPUhqiIIsmkQTCnSIj1DyTtzDwYkQEjCUvBP3UJJMCIkijGkR\nQgiJDTRahBBCYgONFiGEkNhAo0UIISQ20GgRQgiJDTRahBBCYgONFiGEkNhAo0UIISQ2xMZoicit\nInJIRAZF5Otht4cQ4j+FgsJQNoeC0v5neZymJxapDkQkDWAtgFsAHAPwuohsU0r9S7gtI4T4BXNg\nEiPistL6BIBBpdS7SqkxAFsAfDbkNhFCfIR13YgRcTFaHwVwtOz7Y9oxQkhCYV03YkRcjJaRL6DC\nuS0i94vIHhHZc/r06YCaRQjxC9Z1I0bExWgdAzCj7PtLARwvP0EptU4pNV8pNX/KlCmBNo4Q0nhY\ndJIYEQshBoDXAVwpIpcD+DcAdwD4r+E2iRDiJ6mUYHJXG9bfM5913UiJWBgtpVRORL4CYAeANIAn\nlVIHQ24WIcRnWNeNVBObT4FSajuA7WG3gxBCSHjEJaZFCCGE0GgRQgiJDzRahBBCYgONFiGEkNhA\no0UIISQ20GgRQgiJDTRahBBCYgONFiGEkNhAo0UIISQ20GgRQgiJDTRahBBCYoMopezPihkichrA\nexanXAzgTEDNiTLshyLshyLshwuwL4oE2Q9nlFK32p2USKNlh4jsUUrND7sdYcN+KMJ+KMJ+uAD7\nokgU+4HuQUIIIbGBRosQQkhsaFajtS7sBkQE9kMR9kMR9sMF2BdFItcPTRnTIoQQEk+adaVFCCEk\nhiTWaInIrSJySEQGReTrBj9vF5GntZ/vFpGZwbcyGBz0xSdFZJ+I5ETkc2G0MQgc9MPDIvIvIrJf\nRP6viHwsjHb6jYN+eFBEDojIgIj8VER+LYx2+o1dP5Sd9zkRUSISKRVdI3HwmVgsIqe1z8SAiPx+\nGO0EACilEvcPQBrAzwDMAtAG4A0Av1Z1zpcBfF/7+g4AT4fd7hD7YiaAXgAbAXwu7DaH2A83AujU\nvv5SEj8TDvvhorKv+wE8F3a7w+gH7byJAF4B8I8A5ofd7hA/E4sB/FXYbVVKJXal9QkAg0qpd5VS\nYwC2APhs1TmfBfBD7eu/AfA7IiIBtjEobPtCKfVzpdR+AIUwGhgQTvrhRaVURvv2HwFcGnAbg8BJ\nP5wv+7YLQBID307GCAD4FoDvAhgNsnEB47QvIkFSjdZHARwt+/6YdszwHKVUDsAvAUwOpHXB4qQv\nmoF6++FeAP/ga4vCwVE/iMhDIvIzFAfsJQG1LUhs+0FErgYwQyn1d0E2LASc/m0s1FznfyMiM4Jp\nWi1JNVpGK6bq2aKTc5JAs7ynHY77QUTuBDAfwEpfWxQOjvpBKbVWKXUFgGUAHvW9VcFj2Q8ikgLw\nFwD+MLAWhYeTz8T/ATBTKdUL4AVc8FIFTlKN1jEA5TOBSwEcNztHRFoAfAjAuUBaFyxO+qIZcNQP\nInIzgP8GoF8plQ2obUFS7+dhC4DbfG1RONj1w0QAcwG8JCI/B/CbALYlVIxh+5lQSp0t+3tYD2Be\nQG2rIalG63UAV4rI5SLShqLQYlvVOdsA3KN9/TkAO5UWcUwYTvqiGbDtB80d9ASKButUCG0MAif9\ncGXZt/8JwDsBti8oLPtBKfVLpdTFSqmZSqmZKMY4+5VSe8Jprq84+UxMK/u2H8BbAbavgpawHuwn\nSqmciHwFwA4UlTFPKqUOisg3AexRSm0D8AMAT4nIIIorrDvCa7F/OOkLEfkNAP8bwEcA/GcR+ROl\n1JwQm91wHH4mVgLoBvCMpsk5opTqD63RPuCwH76irTjHAbyPC5O7xOCwH5oCh32xRET6AeRQHC8X\nh9VeZsQghBASG5LqHiSEEJJAaLQIIYTEBhotQgghsYFGixBCSGyg0SKEEBIbaLQICQAR2S4iH67j\n/Jki8qafbbJ49lAYzyXECYncp0VI1FBKfSbsNhCSBLjSIqQBiMgficgS7eu/EJGd2te/IyKbROTn\nInKxtoJ6S0TWi8hBEfmJiHRo584TkTdE5DUAD5Xde46I/JNWx2i/iFyp3edfReSHZUlMO8vu87KI\n7BWRHXo2AxG5QkSe046/KiK/qh2/XEReE5HXReRbAXcdIXVBo0VIY3gFwPXa1/MBdItIK4DfAvBq\n1blXAlirZR35BYCF2vG/BrBEKXVt1fkPAlitlOrT7n1MOz4bwDotiel5AF/WnvmXKNZFmwfgSQDf\n0c5fB+APtOOPAPgf2vHVAL6nlPoNAP/utgMICQIaLUIaw14A80RkIoAsgNdQNDDXo9ZoHVZKDZRd\nN1NEPgTgw0qpl7XjT5Wd/xqAPxaRZQA+ppQa0Y4fVUrt0r7ehKKBnI1iotfnRWQAxQztl4pIN4D/\niGKKqgEUcyzq+eSuA7DZ4LmERA7GtAhpAEqpcS0b+O8B+H8A9qNYCfkK1CYXLc8enwfQgWJ5CMOc\nakqp/yUiu1FMXrtDK3X+rsH5SrvPwerVmohcBOAX2mrN8DGWL0hIROBKi5DG8QqKbrdXUFxdPQhg\nwEn1AKXULwD8UkR+Szv0Bf1nIjILwLtKqTUoZt/u1X50mYjoxmkRgJ8COARgin5cRFpFZI5Wjfiw\niNyuHRcRuUq7dhcuJIwuPZeQKEKjRUjjeBVFl9trSqmTKJZor3YNWvF7ANZqQoyRsuOfB/Cm5tb7\nVQAbteNvAbhHRPYDmIRiXGoMxVI7K0TkDQADKLoFgaJBulc7fhAXSqovBfCQiLyOYl05QiILs7wT\nEkNEZCaAv1NKzQ25KYQECldahBBCYgNXWoQQQmIDV1qEEEJiA40WIYSQ2ECjRQghJDbQaBFCCIkN\nNFqEEEJiA40WIYSQ2PD/AdE3eJrO0WE6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50131937d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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r75xup4JL073eQWZIQoiPxLI0zXGD/Dw3AEuerbFTuCOxDpbXYibX/fD1ZBfX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\nw9JHBgayddc1pKvl1HJfREYorw8M5VrKxGB9tlI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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f50127384d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(data, size=6, x_vars='hum',y_vars='cnt' )\n",
    "plt.show()\n",
    "sns.pairplot(data, size=6, x_vars='mnth',y_vars='cnt' )\n",
    "plt.show()\n",
    "sns.pairplot(data, size=6, x_vars='season',y_vars='cnt' )\n",
    "plt.show()\n",
    "sns.pairplot(data, size=6, x_vars='weekday',y_vars='cnt' )\n",
    "plt.show()\n",
    "sns.pairplot(data, size=6, x_vars='workingday',y_vars='cnt' )\n",
    "plt.show()\n",
    "sns.pairplot(data, size=6, x_vars='weathersit',y_vars='cnt' )\n",
    "plt.show()\n",
    "sns.pairplot(data, size=6, x_vars='temp',y_vars='cnt' )\n",
    "plt.show()\n",
    "sns.pairplot(data, size=6, x_vars='windspeed',y_vars='cnt' )\n",
    "plt.show()\n",
    "sns.pairplot(data, size=6, x_vars='temp',y_vars='atemp' )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##由相关度可以看出，气温和租车数强相关，且体感温度与气温大致一至，可去掉气温"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "#数据处理\n",
    "from sklearn.preprocessing import StandardScaler,OneHotEncoder\n",
    "from scipy.sparse import hstack\n",
    "data = data.drop(['instant','registered','dteday','casual'],axis=1)\n",
    "data = data[data.cnt < 8000]\n",
    "data = data[data.cnt > 200]\n",
    "OneHotEnc = OneHotEncoder()\n",
    "##训练数据\n",
    "train_data = data[data.yr ==0]\n",
    "train_data = train_data.drop(['temp','yr'],axis=1)\n",
    "#columns = train_data.columns\n",
    "#columns=np.delete(columns,9,axis=0)\n",
    "ss_X = StandardScaler()\n",
    "ss_y = StandardScaler()\n",
    "x_train1= OneHotEnc.fit_transform(train_data[['season','mnth','holiday','weekday','workingday']])\n",
    "x_train2 = ss_X.fit_transform(train_data[['atemp','hum','windspeed']])\n",
    "x_train = hstack((x_train1,x_train2))\n",
    "y_train = train_data['cnt'].values\n",
    "y_train = ss_y.fit_transform(y_train.reshape(-1, 1))\n",
    "\n",
    "##测试数据\n",
    "train_data = data[data.yr ==1]\n",
    "ss_X = StandardScaler()\n",
    "ss_y = StandardScaler()\n",
    "x_test1= OneHotEnc.fit_transform(train_data[['season','mnth','holiday','weekday','workingday']])\n",
    "x_test2 = ss_X.fit_transform(train_data[['atemp','hum','windspeed']])\n",
    "x_test = hstack((x_test1,x_test2))\n",
    "y_test = train_data['cnt'].values\n",
    "y_test = ss_y.fit_transform(y_test.reshape(-1, 1))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('The r2 score of LinearRegression on test is', 0.6622791169433606)\n",
      "('The r2 score of LinearRegression on train is', 0.8030223936470128)\n"
     ]
    },
    {
     "data": {
      "image/png": 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GxPuo7V14w4BXNnRG0vat1z3U7ie+LiLeCvwY2HdrbygusDPzjVubHhGnA8cD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\nVID/D+G6OUDfbkmMAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5012c72950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f501390e350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "##线性回归\n",
    "from sklearn.linear_model import LinearRegression\n",
    "# 使用默认配置初始化\n",
    "lr = LinearRegression()\n",
    "\n",
    "# 训练模型参数\n",
    "lr.fit(x_train, y_train)\n",
    "\n",
    "# 预测\n",
    "y_test_pred_lr = lr.predict(x_test)\n",
    "y_train_pred_lr = lr.predict(x_train)\n",
    "print('The r2 score of LinearRegression on test is',r2_score(y_test,y_test_pred_lr))\n",
    "print('The r2 score of LinearRegression on train is',r2_score(y_train,y_train_pred_lr))\n",
    "#在训练集上观察预测残差的分布，看是否符合模型假设：噪声为0均值的高斯噪声\n",
    "f, ax = plt.subplots(figsize=(7, 5)) \n",
    "f.tight_layout() \n",
    "ax.hist(y_train - y_train_pred_lr,bins=40, label='Residuals Linear', color='b', alpha=.5); \n",
    "ax.set_title(\"Histogram of Residuals\") \n",
    "ax.legend(loc='best');\n",
    "#还可以观察预测值与真值的散点图\n",
    "plt.figure(figsize=(4, 3))\n",
    "plt.scatter(y_train, y_train_pred_lr)\n",
    "plt.plot([-3, 3], [-3, 3], '--k')   #数据已经标准化，3倍标准差即可\n",
    "plt.axis('tight')\n",
    "plt.xlabel('True cnt')\n",
    "plt.ylabel('Predicted cnt')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The r2 score of RidgeCV on test is 0.6717954578353167\n",
      "The r2 score of RidgeCV on train is 0.8024171492498624\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5012a904d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('alpha is:', 1.0)\n"
     ]
    }
   ],
   "source": [
    "##岭回归\n",
    "from sklearn.linear_model import  RidgeCV\n",
    "\n",
    "#设置超参数（正则参数）范围\n",
    "alphas = [ 0.01, 0.1, 1, 10,100]\n",
    "\n",
    "\n",
    "#生成一个RidgeCV实例\n",
    "ridge = RidgeCV(alphas=alphas, store_cv_values=True)  \n",
    "\n",
    "#模型训练\n",
    "ridge.fit(x_train, y_train)    \n",
    "\n",
    "#预测\n",
    "y_test_pred_ridge = ridge.predict(x_test)\n",
    "y_train_pred_ridge = ridge.predict(x_train)\n",
    "\n",
    "\n",
    "# 评估，使用r2_score评价模型在测试集和训练集上的性能\n",
    "print 'The r2 score of RidgeCV on test is', r2_score(y_test, y_test_pred_ridge)\n",
    "print 'The r2 score of RidgeCV on train is', r2_score(y_train, y_train_pred_ridge)\n",
    "mse_mean = np.mean(ridge.cv_values_, axis = 0)\n",
    "plt.plot(np.log10(alphas), mse_mean.reshape(len(alphas),1)) \n",
    "\n",
    "\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()\n",
    "\n",
    "print ('alpha is:', ridge.alpha_)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The r2 score of LassoCV on test is 0.6685256692816909\n",
      "The r2 score of LassoCV on train is 0.8024953946929864\n"
     ]
    },
    {
     "data": {
      "image/png": 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W2hFgZ2XTh/P87DjcyJbyBvbXtH7Ypqggg4vmjWf+5GzmT8xiznhN8SAiw0fB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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f501398cc50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('alpha is:', 0.000775293710049714)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>coef_lasso</th>\n",
       "      <th>coef_lr</th>\n",
       "      <th>coef_ridge</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>6.244956e-01</td>\n",
       "      <td>[0.7361267523011995]</td>\n",
       "      <td>[0.6346097612811172]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3.510607e-01</td>\n",
       "      <td>[0.4620917211238201]</td>\n",
       "      <td>[0.3623939971517445]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>4.699302e-01</td>\n",
       "      <td>[0.438719615646573]</td>\n",
       "      <td>[0.4771816426698278]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.388969e-01</td>\n",
       "      <td>[0.3748672749981797]</td>\n",
       "      <td>[0.33835122545853424]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2.799009e-01</td>\n",
       "      <td>[0.3333945899694574]</td>\n",
       "      <td>[0.2921721938633054]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4.429960e-02</td>\n",
       "      <td>[0.13837418264745216]</td>\n",
       "      <td>[0.07740517188458607]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1.317254e-01</td>\n",
       "      <td>[0.1255783697793689]</td>\n",
       "      <td>[0.15895562251279574]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.076288e-02</td>\n",
       "      <td>[0.09542436575603203]</td>\n",
       "      <td>[0.11777031321873521]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>[0.079145333215687]</td>\n",
       "      <td>[0.015578733711411052]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2.359520e-01</td>\n",
       "      <td>[0.06871655947642655]</td>\n",
       "      <td>[0.06552098811688391]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2.747930e-02</td>\n",
       "      <td>[0.06371871950816964]</td>\n",
       "      <td>[0.06328502343477622]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>4.180575e-02</td>\n",
       "      <td>[0.022213965464313323]</td>\n",
       "      <td>[0.028167600082166788]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>-1.330509e-02</td>\n",
       "      <td>[0.014244149375678288]</td>\n",
       "      <td>[0.012073268391172176]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>9.569774e-03</td>\n",
       "      <td>[0.0002980408484562744]</td>\n",
       "      <td>[-0.0033950459802101762]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2.678051e-17</td>\n",
       "      <td>[-0.009246309407423868]</td>\n",
       "      <td>[-0.009837303709065881]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>[-0.020019045506402506]</td>\n",
       "      <td>[-0.020558719703952844]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>-1.284967e-01</td>\n",
       "      <td>[-0.056202411317551916]</td>\n",
       "      <td>[-0.1284933259785221]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>-1.941031e-03</td>\n",
       "      <td>[-0.06738966460580333]</td>\n",
       "      <td>[-0.06289077795099822]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>-5.237272e-02</td>\n",
       "      <td>[-0.07821256656715651]</td>\n",
       "      <td>[-0.0767829654458968]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>-5.199766e-02</td>\n",
       "      <td>[-0.07887923713630074]</td>\n",
       "      <td>[-0.07551724243811908]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>-3.430198e-15</td>\n",
       "      <td>[-0.14535253348966237]</td>\n",
       "      <td>[-0.1382490697769464]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>-1.553638e-01</td>\n",
       "      <td>[-0.1553745604151755]</td>\n",
       "      <td>[-0.1565970225326464]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.979148e-01</td>\n",
       "      <td>[-0.16259297458020652]</td>\n",
       "      <td>[-0.100395921915655]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>-1.401705e-01</td>\n",
       "      <td>[-0.17481582161822082]</td>\n",
       "      <td>[-0.11872943519124429]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>-1.907729e-01</td>\n",
       "      <td>[-0.2381129791769629]</td>\n",
       "      <td>[-0.16186784423458092]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>-2.702911e-01</td>\n",
       "      <td>[-0.27227249458165564]</td>\n",
       "      <td>[-0.2700452486720439]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-3.678768e-01</td>\n",
       "      <td>[-0.38112827959532797]</td>\n",
       "      <td>[-0.32826016484331993]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-5.163038e-01</td>\n",
       "      <td>[-0.38433464018725405]</td>\n",
       "      <td>[-0.4284536984216792]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>-4.088248e-01</td>\n",
       "      <td>[-0.4640800119786064]</td>\n",
       "      <td>[-0.3623367458159111]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-5.679345e-01</td>\n",
       "      <td>[-0.6370074193635478]</td>\n",
       "      <td>[-0.5141560460014463]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      coef_lasso                  coef_lr                coef_ridge\n",
       "8   6.244956e-01     [0.7361267523011995]      [0.6346097612811172]\n",
       "9   3.510607e-01     [0.4620917211238201]      [0.3623939971517445]\n",
       "27  4.699302e-01      [0.438719615646573]      [0.4771816426698278]\n",
       "3   2.388969e-01     [0.3748672749981797]     [0.33835122545853424]\n",
       "12  2.799009e-01     [0.3333945899694574]      [0.2921721938633054]\n",
       "7   4.429960e-02    [0.13837418264745216]     [0.07740517188458607]\n",
       "13  1.317254e-01     [0.1255783697793689]     [0.15895562251279574]\n",
       "2   1.076288e-02    [0.09542436575603203]     [0.11777031321873521]\n",
       "11  0.000000e+00      [0.079145333215687]    [0.015578733711411052]\n",
       "16  2.359520e-01    [0.06871655947642655]     [0.06552098811688391]\n",
       "24  2.747930e-02    [0.06371871950816964]     [0.06328502343477622]\n",
       "23  4.180575e-02   [0.022213965464313323]    [0.028167600082166788]\n",
       "18 -1.330509e-02   [0.014244149375678288]    [0.012073268391172176]\n",
       "19  9.569774e-03  [0.0002980408484562744]  [-0.0033950459802101762]\n",
       "26  2.678051e-17  [-0.009246309407423868]   [-0.009837303709065881]\n",
       "20 -0.000000e+00  [-0.020019045506402506]   [-0.020558719703952844]\n",
       "10 -1.284967e-01  [-0.056202411317551916]     [-0.1284933259785221]\n",
       "25 -1.941031e-03   [-0.06738966460580333]    [-0.06289077795099822]\n",
       "21 -5.237272e-02   [-0.07821256656715651]     [-0.0767829654458968]\n",
       "22 -5.199766e-02   [-0.07887923713630074]    [-0.07551724243811908]\n",
       "17 -3.430198e-15   [-0.14535253348966237]     [-0.1382490697769464]\n",
       "29 -1.553638e-01    [-0.1553745604151755]     [-0.1565970225326464]\n",
       "1  -1.979148e-01   [-0.16259297458020652]      [-0.100395921915655]\n",
       "14 -1.401705e-01   [-0.17481582161822082]    [-0.11872943519124429]\n",
       "15 -1.907729e-01    [-0.2381129791769629]    [-0.16186784423458092]\n",
       "28 -2.702911e-01   [-0.27227249458165564]     [-0.2700452486720439]\n",
       "6  -3.678768e-01   [-0.38112827959532797]    [-0.32826016484331993]\n",
       "0  -5.163038e-01   [-0.38433464018725405]     [-0.4284536984216792]\n",
       "5  -4.088248e-01    [-0.4640800119786064]     [-0.3623367458159111]\n",
       "4  -5.679345e-01    [-0.6370074193635478]     [-0.5141560460014463]"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Lasso／L1正则\n",
    "from sklearn.linear_model import LassoCV\n",
    " \n",
    "lasso = LassoCV()  \n",
    "\n",
    "#训练\n",
    "lasso.fit(x_train, y_train)  \n",
    "\n",
    "#测试\n",
    "y_test_pred_lasso = lasso.predict(x_test)\n",
    "y_train_pred_lasso = lasso.predict(x_train)\n",
    "\n",
    "\n",
    "# 评估，使用r2_score评价模型在测试集和训练集上的性能\n",
    "print 'The r2 score of LassoCV on test is', r2_score(y_test, y_test_pred_lasso)\n",
    "print 'The r2 score of LassoCV on train is', r2_score(y_train, y_train_pred_lasso)\n",
    "mses = np.mean(lasso.mse_path_, axis = 1)\n",
    "plt.plot(np.log10(lasso.alphas_), mses) \n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()    \n",
    "            \n",
    "print ('alpha is:', lasso.alpha_)\n",
    "\n",
    "# 看看各特征的权重系数，系数的绝对值大小可视为该特征的重要性\n",
    "columns = train_data.columns\n",
    "columns=np.delete(columns,9,axis=0)\n",
    "fs = pd.DataFrame({ \"coef_lr\":list((lr.coef_.T)), \"coef_ridge\":list((ridge.coef_.T)), \"coef_lasso\":list((lasso.coef_.T))})\n",
    "fs.sort_values(by=['coef_lr'],ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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